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Conceptual variation: Gendered differences in the lexicalization of the concept of commodity in environmental narratives

Conceptual variation: Gendered differences in the lexicalisation of the concept of COMMODITY in environmental narratives

by Justyna A. Robinson, Rhys J. Sandow, Albertus Andito

An updated version of this work can be found as Chapter 10 in: Justyna A. Robinson; Rhys J Sandow, & Albertus Andito. (2026). “Conceptual variation: Gendered differences in the lexicalization of the concept of COMMODITY in environmental narratives”. In Rhys J. Sandow & Natalie Braber (Eds) Sociolinguistic Approaches to Lexical Variation in English. 173-193. Routledge.

Abstract

Within studies of lexical meaning, conceptual variation has received little attention, possibly due to methodological difficulties with operationalising concepts. In the current paper, we build on the approach developed by Robinson & Weeds (2022) to study gendered variation in the lexicalization of concepts in environmentally-themed directives from the Mass Observation Project. We broadly define a concept as a cluster of (near-)synonymous and hyponymic terms representing a shared meaning. Previous research (Robinson & Weeds 2022) shows that gendered variation exists in collocational patterns of concepts. In the current paper, we focus on the varied ways in which a concept is lexicalized by men and women. A case-study of the concept of commodity shows that taxonomic differences between genders exist, with women using more specific terms to a greater extent than men. We suggest that the socially-variable articulation of concepts represents differences in speakers’ attention afforded to given commodities represented by the concept of commodity.

Keywords: conceptual variation, keyconcept, keysense, lexis, lexicalisation, sociolinguistics, gender, Mass Observation Project

1. Introduction

Variation in lexical meaning is typically investigated from the broad perspectives of semasiology and (formal) onomasiology.¹Semasiology refers to the mapping of a single word form onto multiple senses, for example, wicked ‘evil’ and ‘good’. Formal onomasiological variation investigates the distribution of a plurality of words that are used to lexicalize a given meaning at the level of (near-)synonymy, for example, sofa is lexicalized as sofa, settee, and couch. This latter type of lexical variation is the one that has most widely been studied from a sociolinguistic perspective (see Sandow & Braber, this volume). However, the focus of this chapter is on conceptual onomasiological variation (for example, Grondelaers & Geeraerts 2003), that is, the way in which concepts are distributed and lexicalized in heterogenous ways.

There is a spectrum of methodological approaches to lexical variation that vary according to the degree of control that the researcher has over the lexical usage in the data that they work with. At one end of the spectrum where control is highest, researchers use elicitation tasks, including surveys (for example, Britain et al. this volume; Robinson 2010, 2012). Lexical variation can also be attested through semi-structured interviews (for example, Braber, this volume; Bucholtz 2012). At the other end of the spectrum, there are data which had been produced with no agency of researchers, such as newspaper articles, radio recordings. Such work typically engages with methods of Corpus Linguistics (for example, see Wilson this volume).

The development of Corpus Linguistics has allowed for investigating another layer of lexical variation, i.e. variation in meaning between texts more broadly as opposed to the formal onomasiological variation that relies on functional equivalence between variants. This is typically achieved through a keyword analysis (for example, see Baker 2004). Such analysis involves profiling a target dataset against a baseline and identifying those words (or phrases) that are distinctive of the target data. Keyword analysis offers a powerful approach in identifying the ‘aboutness’ (Kilgarriff 2009) of texts in a bottom-up fashion. However, this method profiles word forms, not their meanings. Subsequently, it is up to a researcher to conduct a post hoc, and often ad hoc, interpretation of the meanings from a keyword list in search for meaningful themes in the text.

In this paper, we apply a method for extracting semantic variation between texts by analysing meanings of words, rather than just lexical forms (à la keywords). We access linguistic meaning through the unit of concepts which we broadly define as a cluster of (near-)synonymous and hyponymic terms representing a given meaning. The principle of this method was first introduced by Robinson & Weeds (2022) and Robinson et al. (2023). In that work, Natural Language Processing tools are applied to analyse conceptual variation between texts through introducing the notion of a keyconcept.² A keyconcept is a concept that occurs more often in a corpus than expected, as compared to a reference corpus (see Section 4 Method for a mathematical clarification of the definition). This approach allows for semantic and statistical interpretation of concepts that are characteristic of a given text.

Previous research shows that the distribution of conceptual themes in the language used by gender groups is not homogenous. Based on text samples from 70 studies the United States, New Zealand, and England, Newman et al. (2008: 219–20) found that compared to women, men were more likely to talk about sports, money, occupation and less likely to talk about home, family, and friends. For a more detailed discussion of language and gender, including the related differences in socialisation practices, see Eckert & McConnell-Ginet (2013). Robinson & Weeds (2022) also discovered the existence of variation in concepts used by male and female witnesses in courtrooms as well as differences in conceptual collocation patterns across genders. In the current research, we ask if the gendered language also varies in terms of conceptual taxonymy. More specifically, we consider if men and women lexicalize concepts differently, that is, whether they engage with specific or general levels of a conceptual hierarchy, i.e. hyponymy vs. hypernymy, to differing extents.

The paper is structured as follows. First, we contextualise the current study within the growing body of work on concepts and lexicalization. Next, we explain the methodological approach that enables a conceptual analysis. Then, we turn to the dataset, which is the Mass Observation Recycling and Environmentalism (MORE) corpus. It consists of responses to three ‘directives’ on the topic of environmentalism collected by the Mass Observation Project. The analysis profiles the concepts within the dataset, including variation between men and women, using the concept of commodity (specifically commodity.n.01) as a case study. The choice of environmental narratives and the concept of commodity is motivated by the desire to understand better the characteristics of populations’ language and thinking in this economically- and socially-important area. We show the ways in which such a conceptual perspective highlights gender-based differences in behavioural practices such as that women engage with more concepts that pertain to domestic labour. We also identify variation in the lexicalization of concepts, with women typically using more specific (hyponymic) levels of the conceptual hierarchy than men. The analysis benefits from a range of visualisation tools. We conclude by advocating for the value of conceptual analysis and the opportunities it affords for lexical variation research. We note that this research is exploratory and serves as a proof-of-concept approach to the analysis of socially-variable patterns in lexicalization of concepts.

2. The Concept and Lexicalization

The last decade has seen an increased focus on concept-led linguistic research. One area that has led investigations into concepts is language change. A body of conceptual research has built on established historical thesauri, such the Bilingual Thesaurus of Everyday Life in Medieval England (BTh, Sylvester et al. 2017) or the Historical Thesaurus of the Oxford English Dictionary (HT, Kay et al. 2023), or on large corpora as in the Linguistic DNA project (Fitzmaurice et al. 2017).

Variation exists in the way the unit of a concept is operationalised in the studies of language. The HT and BTh operationalise concept as a sense or a group of senses expressed by a term or terms and placed within a taxonomic structure with other meanings. The HT presents a taxonomy which begins with the most general ways of expressing a concept, such as categories of The World, The Mind, Society, and moves hierarchically downwards to the most specific [ones]”.³ The HT takes the structure of Roget’s Thesaurus and imposes it on historical data, with a sensitivity to representing historical senses of words.The BTh draws on the HT structure with modifications that are suitable to mirror the medieval world. However, BTh classifies vocabulary into semantic roles, rather than a hierarchy.

A departure from this view of concepts is presented by the Linguistic DNA project which sees concepts as discursive clusters. According to Fitzmaurice et al. (2017: 25) “In any particular historical moment, a concept might not be encapsulated in any single word, phrase or construction; instead it will be observable only via a complete set of words, phrases or constructions in syntagmatic or paradigmatic relations to each other in discourse”. A discursive concept is made up of paradigmatic terms which habitually co-occur in language across large proximity windows. For example, Mehl (2022) shows that the discursive concept diversity-opinion-religion is made up of terms diversity, opinion, religion habitually co-occurring around 5000 times in EEBO-TCP. In other words, a frequent and mathematically significant occurrence of the trio diversity-opinion-religion indicates a possibility of an existence of an idea that was expressed by these three nouns in conjunction rather than by an individual term. Close reading of extracts representing the discursive concept allows for tracing the formulation of ideas regardless of whether they ever become encapsulated in a single term.

Language change research also pursues questions of modifications of different levels of conceptual hierarchy that happen as an outcome of language contact. Sylvester et al. (2022) show that terms making up conceptual categories get reorganised when distinct communities come to contact. In research querying the absorption of French-origin borrowings into Middle English, Sylvester et al. (2020: 28) show that these borrowings tended to enter hypernymic (more general) levels of conceptual categories. Surprisingly, these French tended to occupy semantic spaces where there was more, not less, lexical choice. In research exploring the obsolescence, Vogelsanger (2024: 24) finds that most lexical loss happens also at hypernymic levels as “the more specific the concept, the fewer words and senses we find, but in turn they seem to be more resilient, since they show much lower rates of obsolescence”.

A significant area of study focuses on lexicalization of concepts. While lexicalization generally refers to “the assignment of lexeme to a meaning” (Murphy 2010: 16), historical linguists tend to focus on various aspects of this process. Thus, Trousdale (2008) asks how once closed-class words or phrases develop lexical meaning. Alexander (2018) or Dallachy (2024) investigate how words that map new concepts are added to a language’s lexicon. Sylvester and Tiddeman (2024) develop measures of density of lexicalization. These studies show potential for using a conceptual view on language as a way making exploring social cognition, with lexicalization being a measure of “cultural attention” (Alexander 2018, Dallachy 2024) and a “function of speakers’ needs” (Sylvester et al. 2020: 28).

The approach to concept and lexicalization pursued in the current work can broadly be categorised in the tradition of the aforementioned thesauri-based approaches in that we consider a term’s usage, its sense, as a base for a concept. We also consider the concept as belonging to a network of hierarchically-structured meanings, i.e. structured horizontally in terms of (near-)synonymy and co-hyponymy and vertically in terms of hyponymy and hypernymy. We use WordNet (Fellbaum 1998), specifically WordNet 3 (Princeton University 2010), to profile senses and model the conceptual structure including semantic relations. WordNet has the advantage in this respect as it is made up of twenty hierarchical levels (Mohamed & Oussalah 2014), as opposed to, for example, the seven levels of the Historical Thesaurus (Piao et al. 2017), thus it enables greater granularity of analysis when it comes to researching hierarchical semantic relations.

WordNet is a large lexical database of English that groups words according to their meaning. It enables meaning to be modelled through two main semantic units, senses and concepts. Working at the sense level means that we consider words in a text by their meaning as tagged by WordNet. Concepts additionally include all of the hyponyms of the sense. As an illustration of the difference between a sense and concept, consider the WordNet tag of person.n.01, which is defined as ‘a human being’.⁴ The sense person.n.01 is lexicalized by words that are sense-tagged as person.n.01, including person, individual, someone, and somebody. These lemmas exist at a single level of the semantic hierarchy, that is, the semantic relationship between them is broadly that of synonymy. Meanwhile the concept person.n.01, refers to the words that are sense-tagged as person.n.01 and to words that are sense-tagged as the hyponyms of person.n.01, which include the co-hyponyms child.n.03 and adult.n.01, hyponyms of these hyponyms, such as woman.n.01, recursively until there are no more hyponyms left. This process is unidirectional, that is while the concept of person.n.01 includes hyponyms such as adult.n.01, it does not include hypernyms such as organism.n.01.

The proposed view of text semantics, in which each word is tagged for its sense and position in the WordNet hierarchy allows for testing a whole set of hypotheses on categorisation of meaning, concepts, and lexicalization. The current research centers lexicalization understood as the ways in which concepts are represented through words or multi-word constructions. We investigate gendered variation in using terms at hypernymic and hyponymic levels in the concept of commodity.

In identifying the scope of this research, we are motivated by methods and findings of Robinson & Weeds (2022) on conceptual gendered variation. Robinson & Weeds (2022) discover that in the 19^th century concepts varied in terms of their differing collocational patterns across genders. For example, while the concept of woman was used at similar frequency by male and female speakers, the adjectival concepts that the concept woman collocated with demonstrated variation across gender. Women were more likely than men to describe other women using the concept AP.02.b [individual character] and the concept AW.04.a [poverty]. These concepts include adjectives such as single and poor and their usage with the concept woman is evidenced by statements such as ‘She is a married woman’ and ‘I am a poor unfortunate woman’ (Robinson & Weeds 2022: 421). Unlike Robinson & Weeds (2022) who focus primarily on collocation patterns, we focus on the ways in which men and women lexicalize concepts and the different levels of the conceptual hierarchy with which they engage.

3. Data

Data used in this research are provided by the Mass Observation Project (Mass Observation 2010, henceforth MOP), a British national life-writing project. Thrice yearly, the MOP issue open-ended questionnaires, or ‘directives’, on a variety of topics, from Royal coronations, to attitudes towards gender. These are sent to a panel of c.500 ‘observers’ who are invited to submit their response to the directive. We focus on a collection of three directives with a broad theme of environmentalism, which are titled ‘Future of consumption’ (2018), ‘You and plastics’ (2019) and ‘Household recycling’ (2021) (see here). The ‘Future of consumption’ directive asked participants to consider the way in which consumption practices are likely to change for future generations. ‘You and plastics’ directive asked observers to reflect on their use of, particularly single-use, plastics in the past, present, and future. ‘Household recycling’ directive asked respondents to consider what and how often they recycle, as well as their motivations for recycling. While each Mass Observation directive receives a small number of handwritten responses, we focus on digitally-submitted files. These responses to the three directives number 395 submissions from ‘observers’, totalling 416,754 words. These three directives form the target corpus, henceforth the Mass Observation Recycling and Environmentalism (MORE) corpus.

Senses and concepts become key if they occur frequently enough in a target corpus in comparison to a reference corpus. The choice of a reference corpus depends on a rage of criteria (cf. Baker 2004). In the current research the reference corpus comes from data collected by the MOP. As well as the directives, the MOP also issues calls for ‘Day diaries’ on the 12^th of May each year since 2010. These diaries include descriptions of daily activities, thoughts that the writer has throughout the day, and generally provide an insight into the life of the diarists. The digitally-submitted responses to these diaries from 2010–2019 form the baseline with 4,101,605 words, from 3,070 diary entries (see Robinson et al. 2023).

Consistently, the respondents to the MOP’s calls are disproportionately women, older, middle-class and from the South-East of England (see Robinson et al. 2023). In terms of gender, participants are asked to self-identify their gender, and some do so with labels outside of the male-female binary.⁵ While the unbalanced nature of the sample is a limitation, the size of the dataset and subsets for each demographic group still allow for a robust comparative analysis. Excluding those for whom relevant data was not provided, the gender and the decade of birth distribution of the contributors to both the target and reference corpora are presented in Figure 1. The two datasets in Figure 1 are broadly similar in relation to socio-demographic categories, although the MORE corpus (left) has slightly more male respondents (28.8%) as opposed to the baseline (right, 17.7%).

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4. Method

In the current research, Word Sense Disambiguation (WSD) is employed to determine which sense is the most appropriate for each word in the data based on the word’s context. We use SupWSD (for more detail, including an evaluation of its accuracy, see Papandrea et al., 2017), a WSD tool that uses a machine learning algorithm, i.e. Support Vector Machine, and WordNet (Fellbaum 1998, WordNet 3.0 (2010)) as the sense inventory, taking into account part-of-speech, surrounding words, and local collocations.

Unlike other knowledge bases (for example, the HT), the WordNet hierarchy only applies to nouns and verbs. While other part-of-speech categories, such as adjectives and adverbs are tagged for senses in WordNet, they do not form a hierarchy, that is, they are represented in a horizontal dimension only. Thus, the current conceptual analysis is limited to verbs and nouns. Verbal and nominal senses are assigned a level, ranging from the broadest concepts at level 0, to steadily more specific concepts at levels with higher numbers. At level 0, the highest level of hyponymy, a variety of verbs, such as those tagged with senses trade.v.01 and degrade.v.01, are present, while all nouns converge on entity.n.01. At the other end of the hierarchy, there are much more specific senses, such as cow.n.01 at level 17. That is, there are 16 hypernyms⁶ that separate cow.n.01 and entity.n.01, for example, physical_entity.n.01 at level 1 and cattle.n.01 at level 16.

After each word in the corpora has been tagged by the appropriate sense, we perform analyses of the corpus through a bespoke Application Programming Interface. In order to identify differences in the usage of a senses or in the use of concepts between the target and reference corpora we use a measure of Pointwise Mutual Information (PMI, see for example, Huang et al. 2009, for a discussion of its application to conceptual analysis, see Robinson & Weeds 2022, Robinson et al. 2023). PMI enables the identification of keysenses and keyconcepts, i.e. senses or concepts which appear in the corpus more often than one would expect, given their frequency in a reference corpus. The higher the PMI, the more distinctive the sense or the concept of the target dataset relative to the reference corpus. The PMI is established in the way presented in Equation 1, where A is a sense or concept, B is a target corpus, P(A|B) is the probability of encountering a sense A or a concept A given a target corpus B, and Pref(A) is the probability of a sense A or concept A in the reference corpus.

\[ \text{PMI}(A, B) = \log \left( \frac{P(A \mid B)}{Pref(A)} \right) \]

... Equation 1

In Section 5.1, using the tools discussed here, we explore the semantics of the MORE corpus. More specifically, we provide an overview of the distinctive senses and distinctive concepts. In Section 5.2, we focus on the case study of the concept of commodity to answer questions pertaining to taxonomic differences in lexicalization patterns between men and women.

5. Results and Analysis

5.1. Semantics of the MORE corpus: Keysenses and keyconcepts

In order to provide a semantic overview of the environmental narratives, we identify top keysenses and a conceptual profile of the data. The top 50 keysenses in the MORE corpus, which are measured against the senses in the reference corpus, are presented in Figure 2. The senses with the highest PMI values appear in the top left with the largest tile size and darkest colour, conversely, the 50^th top sense appears in the bottom right with the smallest tile size and palest colour. The sense-level analysis clusters (near-)synonymous lexical items. For example, in some cases the adjectives reusable and recyclable are used synonymously enough to be tagged with the same sense, i.e. reclaimable.s.01.⁷ Additionally, this analysis disambiguates polysemous words and is preferable when the focus is on the meaning rather than form. For instance, it distinguishes between waste.n.01 ‘any materials unused and rejected as worthless or unwanted’ and waste.n.02 ‘useless or profitless activity; using or expending or consuming thoughtlessly or carelessly’.

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Figure 10.2 provides a semantic overview of the MORE corpus. The most distinctive sense of the corpus is coronavirus.n.01. This result occurs due to the very low frequency of this sense in the baseline corpus, coupled with its much higher frequency in the target corpus, particularly the ‘Household recycling’ directive, where the directive prompt specifically asked about the effect of Covid‑19 on recycling practices. Other senses provide a largely intuitive account of the content of the responses to the three directives, such as materials, for example, plastic.n.01, cardboard.n.01, and cellophane.n.01, as well as practices associated with environmentalism, such as recycle.v.02 and flatten.v.01.

The keyconcept approach develops a keysense analysis by considering (near-)synonymy alongside hyponymy. One way to visualise the verbal and nominal concepts in the target corpus is by using a sunburst, as in Figure 3.⁸ This conceptual profile presents the concepts at all levels of the conceptual hierarchy. Each level in conceptual hierarchy corresponds to one ring on the sunburst, with the highest levels the conceptual hierarchy, such as entity.n.01, being close to the centre of the figure at level 0, then its daughter nodes physical_entity.n.01 and abstraction.n.06 at level 1, and so on.⁹ Hyponyms radiate out from their parent node. However, where the sense of the parent node is used, this does not generate a daughter node and is, instead, represented by empty space. For example, in the concept container.n.01 on the right of Figure 3 at level 6, the nodes that radiate from this concept highlight that is has a variety of hyponyms, such as, vessel.n.03 and bag.n.01. However, there is also space not occupied by daughter nodes, this is where the sense container.n.01 was used directly. The colour and size of each node are also meaningful dimensions of this visualisation. The size of each node represents raw frequency of concepts in the target corpus, and the intensity of colour indicates each concept’s PMI value. The bar on the right of the figure provides a guide as to the PMI range. For example, matter.n.03 is less frequent but more distinctive in the target corpus than object.n.01 (both concepts are at level 2). While it is not intended that each node should be readable, the figure serves as a compass, directing the researcher to the most distinctive conceptual areas of the dataset. For example, at the more general levels of the conceptual hierarchy (for example, 0–3), the PMI values are very low. However, distinctiveness is more likely to be found at lower levels of the hierarchy. For example, container.n.01 has a particularly high PMI (2.8) at level 6, as a hyponym of instrumentality.n.01. However, this high PMI is not simply a result of the sense container.n.01, but of its hyponyms, too. Within container.n.01 some of its daughter concepts also display high PMIs, such as bottle.n.01 (PMI=4.5) and bin.n.01 (PMI=5.72).

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Given that the environmentally-themed directives make up the MORE corpus, it is not surprising that the respondents discuss types of containers and their uses, including innovative repurposing, as well as their recycling practices. However, not all daughter concepts of container.n.01 are highly distinctive. For example, bath.n.01 and boiler.n.01 occur less often than in the baseline. Other concepts with particularly high PMI values include use.n.01 (PMI=4.4), and its daughter concept recycling.n.01 (PMI=6.2), and waste.n.01(PMI=4.8) and its daughter concept rubbish.n.01 (PMI=3.3).

This current section illustrates an approach to semantic characterisation of data. The MORE corpus is semantically described from the perspective of senses and concepts. Figure 2 shows the most distinctive senses of the MORE corpus, including lockdown.n.01, pandemic.n.01, and plastic.s.02. The conceptual approach complements this by considering the taxonomic relation of hyponymy. For example, while a sense-level analysis highlights container.n.01 in the top 50 most distinctive senses, a conceptual analysis shows how not only is this sense distinctive of the corpus, but so are some of its hyponyms such as bin.n.01 and botte.n.01.

5.2. Gendered variation in the MORE corpus: Keyconcepts and lexicalization patterns

Having established the semantic characteristics of the MORE corpus through the keysense and keyconcept analysis, we turn to the question of gendered semantic variation. Firstly, we investigate conceptual differences in environmental narratives between male and female respondents. Secondly, we ask how lexicalization of a concept, commodity, varies across gender groups.

Gendered differences in concepts used in the MORE corpus are extracted through a keyconcept analysis. Each concept’s PMIs for each gender is measured against the other gender group within the MORE corpus.¹⁰ That is, when the female data are the target, the male data are the reference, and vice-versa (see Figures 4 and 5).

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Relative to men, for women, the PMI of charity.n.01 is 1.4, husband.n.01 is 3.6, and home.n.01 is 1.3. Relative to women, for men the PMI of internet.n.01 is 1.2, alcohol.n.01 is 1.1, and wife.n.01 is 4.1 highlighting that men engage with these concepts to a greater extent than women do in the MORE corpus. Such results testify to heterogenous behaviours and practices across genders.

Even when concepts have similar overall rates of usage across demographic groups, their internal structure can also differ. This is exemplified through the concept of commodity.n.01 which is selected as a case study. This concept is used similarly by men and women in the dataset as measured by PMI. It is used very slightly more by women with a PMI=0.18, when compared with men. The raw frequency of usage is N=1021 for women, and N=445 for men. While the PMI for commodity.n.01 for both genders is similar, the internal structure of the concept displays a great deal of variation across the two gender groups. The conceptual profile for commodity.n.01 among female writers is presented in Figure 6, while the male equivalent is presented in Figure 7.

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The conceptual profiles for males and females display a number of differences in the type of artifacts with which males and females interact. Numerous examples of gendered clothing items are distributed disproportionately across the gendered groups, with concepts such as dress.n.01 (PMI= 0.3), negligee.n.01 (PMI=0.9), brassiere.n.01 (PMI=1.7), and skirt.n.02 (PMI=0.1) displaying positive PMIs in the female data, and suit.n.01 (PMI=2.2) and jean.n.01 (PMI=1.8) displaying positive PMIs in the male data. There is also a greater attention paid to domestic labour evident in women in the conceptual profiles of commodity.n.01. For example, white_goods.n.01 is used more by women (PMI=0.8). Within the concept of white_goods.n.01, the female data has positive PMIs for refrigerator.n.01 (PMI=0.5), dishwasher.n.01 (PMI=2.0), and washer.n.01 (PMI=2.2), while the only hyponym with a positive PMI in the male data is cooler.n.01 (PMI=1.8). Similarly, laundry.n.01 has a positive PMI in the female data (PMI=1.1). There are also examples of the asymmetric distribution of childcare, with diaper.n.01 (PMI=2.8) having a positive PMI in the female data.

One surprising result is that shirt.n.01 is used more by the female observers (PMI=0.82), despite it being an artifact stereotypically associated with men. However, we can account for this result by identifying that many of these examples involve accounts of interactions with male clothing by women, such as Example (1):

I reuse my husband’s cotton shirts in crafting. [Household recycling, female born in the 1960s]

The observed differences in conceptual profiles for males and females suggest that concepts provide a window into community behaviours. The artifacts represented by the concept of commodity and the asymmetric gender distribution with which they are engaged with, are a medium through which the physical world is experienced by men and women.

Another perspective in which the current research highlights gendered conceptual variation is through taxonomic differences, i.e. the levels of the conceptual hierarchy that men and women typically engage with. This differential engagement is evident in the fact that the sunburst in Figure 6 is noticeably ‘busier’ than the one in Figure 7. That is, the male data in Figure 6 includes more empty space, that not occupied by daughter nodes (hyponyms). Take clothing.n.01 as an example. Proportionally, men are more likely to use the more general level sense clothing.n.01, while women are more likely to conceptualise clothing with a greater degree of specificity. When the concept clothing.n.01 is used, men use the sense clothing.n.01 32.2% of the time, compared to 24.7% for women. Thus, women are more likely to use a hyponym. To illustrate this, example (2) is more typical of a male conceptualisation of clothing.n.01 at the more general category level, whereas the Example (3) is more typical of a female conceptualisation at a greater level of specificity (brassierre.n.01):

Used batteries are taken to local supermarkets where they can be recycled, also clothing can be recycled at various points around the area. [Household Recycling, male born in the 1950s]
I’d like to be able to recycle old bras [Household Recycling, female born in the 1950s]

Similarly, the use of concept of merchandise.n.01 is more likely to be realised as a hyponym by women, rather than men. For women 74.2% of uses of this concept are in the sense merchandise.n.01 and for men this value is higher at 81.6%. This is also true of the broader concept of commodity.n.01, with men using the sense commodity.n.01 17.9% of the time, compared with 12.4% for women.¹¹

The internal structural differences in concepts evidence variation in the ways men and women express those concepts by their use of words, that is, in the ways they lexicalize those concepts. In the analysis of commodity.n.01, differences arise in the levels within the conceptual hierarchy at which concepts are lexicalized, with men lexicalizing concepts at more generic levels, and women lexicalizing concepts at more specific levels.

6. Summary and Conclusions

This research presents a new approach to querying semantics of texts by engaging with horizontal ((near-)synonymous and co-hyponymic) and vertical (hyponymic and hypernymic) semantic relations. The current approach highlights hyponymy as a critical aspect of language variation alongside more widely-research relations in socio-semantics, such as synonymy and polysemy. Exploring texts through the lenses of keysense and keyconcept enables semantic content to be profiled which can empirically navigate further analysis and close reading. In one way, the concept-driven approach is more specific than more traditional alternatives, such as the keyword analysis, in that it distinguishes polysemous senses of the same word form. In another way, it is more general as in a conceptual approach, it is less relevant which (near-)synonym is used, what matters is the meaning expressed. This perspective enables the analysis to centre meaning, while variation in word form is secondary to this approach. We advocate for using the current conceptual approach that offers a bird’s-eye view of the text meaning with conjunction with close reading in order to develop the most robust insights into a text’s semantics (for example, Robinson et al. 2023).

The current research demonstrates the ways in which a conceptual perspective can tell stories of socially-asymmetric behavioural practices. Examples of this include the way in which the use of clothing items exhibit gendered patterns, such as brassiere.n.01 being used relatively more by women and suit.n.01 by men. Similarly, there is a higher frequency of concepts pertaining to domestic labour and childcare in the female data. Results that testify to heterogenous behaviours and practices across genders are corroborated by the parallels with other studies, such as those observing gender-based differences in the share of domestic duties (Bianchi et al. 2012; Thébaud et al. 2021). The parallels between such previous and the current research speak to the validity of this approach.

The current concept-driven approach enables insights into lexicalization. Even when concepts have similar overall rates of usage across demographic groups, their internal structure can also differ. We show that men and women differ in the way they use different levels of conceptual hierarchy when they express or lexicalize the same concept. In the case of commodity.n.01. men are more likely to use general levels terms, such as, clothing, women are more likely to engage with more precise classifications in their lexicalization, that is, specific types of clothing, such as, bra. This idea is redolent of Lakoff’s (1973) suggestion that women tend to use more specific colour terms, such as, lavender, whereas men lexicalize these same colours at a broader level of conceptualisation, such as, purple.¹² Lakoff’s (1973) observations alongside the current research lead us to hypothesise that differential lexicalisation patterns may hold for gendered or socio-demographic conceptual variation more broadly.

Another question to consider is why lexicalization would take place at different levels of the conceptual hierarchy for men and women. One possibility lies in the notion of cultural and social needs speakers express via lexicalisation practices (cf. Alexander, 2018, Dallachy 2024, Sylvester et al. 2020). Another possibility considers engaging with cognitive foundations of language and perception biases among men and women. At this stage, we suggest that the lexicalization of commodity.n.01 reflects the attention afforded to the artifacts with which men and women engage. The question of why the lexical representations of objects display differential attention across community could to be explored further via socio-cognitive research frameworks (Pütz et al. 2014).

Findings of the current research have implications for language used by policy and industry decision-makers in the climate and environmentalism space. By integrating insights from the Nudge Theory, especially the idea of “choice architecture” (Thaler and Sunstein 2008), relevant communication and engagement strategies can be optimised to a specific audience. By using gender-characteristic language, such as a more general or detailed terms to describe commodities, population can be gently steered towards a desired behaviour, such a more accurate sorting of those commodities when they become waste. The policy makers also require precise categorisation in waste management (EU Waste Framework 2008/98/EC)¹³, which the current research provides through the categorisation of commodities people handle. By fine-tuning public communication to resonate with socio-demographic groups, and embedding this clarity into policy wording, policy makers can more effectively reduce landfill waste. These strategies work together to create an environment where an individual is gently steered toward more sustainable behaviour without the need for overt financial incentives.

To conclude, the proposed concept-led approach shows potential beyond a case of gendered variation. The current analysis could apply to any demographic category, including cross-sectional categories. It remains to be seen the extent to which the presented results hold for other concepts in a systematic way. Also, motivated by studies outlined in Section 2, such as Sylvester et al. (2020) or Vogelsanger (2024), further research could explore the relationship between lexicalization and different levels of the conceptual hierarchy in the context of language change. While it is argued elsewhere (for example, Sandow & Braber, this volume), that lexis can provide a lens into society, we argue here that a conceptual approach lends a particularly felicitous perspective to this endeavour. The proposed conceptual approach affords further methodological, theoretical, and applied opportunities in sociolinguistics and beyond.

Footnotes

Acknowledgements: We would like to thank two anonymous Reviewers for their helpful comments on the earlier draft of this manuscript. We would like to thank the broader team at Concept Analytics Lab at the University of Sussex, particularly Julie Weeds, Willam Kearney, Yassir Laaouach, and Ray Davey for the work on the API that underpins the research presented here. Supported by the Arts & Humanities Research Council (AHRC) Impact Acceleration Account, at the University of Sussex (AH/X003531/1).↩︎
Robinson & Weeds (2022) use the term characteristic concept.↩︎
https://ht.ac.uk/classification/↩︎
In the WordNet sense inventory, the refers to the nominal part-of-speech category. The 01 identifies this as the first sense of this form in WordNet. By way of example, person.n.01 is defined as ‘a human being’ and person.n.02 is defined as ‘a human body (usually including the clothing)’.↩︎
Figure 1 does include these individuals, but as there are very few in number, they are not clearly visible.↩︎
These are hypernyms from the perspective of cow.n.01, but hyponyms from the perspective of entity.n.01.↩︎
For example, ‘The video I watched suggested that rice and pasta should be stored in reusable glass containers’ [‘Future of consumption’ directive, male born in the 1970s] and ‘some of the plastic containers are recyclable but I guess that several are single-use’ [‘You and plastics’ directive, female born in the 1930s].↩︎
Concepts with a negative PMI also appear in Figure 3 and 4. In terms of the colour coding key on the figures, these are coloured as if their PMI value is 0.↩︎
The highest levels in the conceptual hierarchy correspond to lowest numbers in the WordNet hierarchy. Thus, the highest levels are entity.n.01 at level 0, physical_entity.n.01 at level 1 and so forth.↩︎
This task requires a modification of the PMI Equation (1) in terms of target and reference datasets.↩︎
Beyond the concept of commodity.n.01, this effect holds for other concepts where men are more likely to use the broader sense and women are more likely to use a hyponym. For example, in the concept of child.n.02, men refer to the specific sense 53.6% of the time, compared to 40.7% for women; in chemical.n.01 the values are 3.9% for men, 1.9% for women, and in waste.n.01, the values are 76.9% for men and 71.2% for women. ↩︎
We thank an anonymous Reviewer for this observation.↩︎
https://eur-lex.europa.eu/eli/dir/2008/98/oj/eng, see especially Paragraph 2.↩︎

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About Us

We identify conceptual patterns and change in human thought through a combination of distant text reading and corpus linguistics techniques.

Blog

Looking back: What the Mass Observation Covid-19 diaries can teach us?

“Show me the meaning of being lonely”

How language reveals different faces of loneliness?

‘We’re saying that we trust them but really we don’t’: The discursive framing of TRUST in international trade deals

How language reveals different faces of loneliness?

How language reveals different faces of loneliness

by Justyna A. Robinson, Gayathri Sooraj, and Caitlin Hogan

The issue of loneliness has been discussed in public platforms more frequently in recent years. Just within the past week newspapers have talked about student loneliness, male loneliness, loneliness epidemic. A recently published WHO Report on Social isolation shows that 1 in 6 people globally suffers from loneliness. The data on loneliness in the UK shows that nearly half of adults feel lonely occasionally, sometimes, often, or always (see here). Some groups are especially at risk of loneliness, such as, young, disabled people (see here). However, the available reports rarely dive into exploring how people themselves describe loneliness or what language choice people make when they talk about loneliness (but see here). These questions are explored by Justyna Robinson (Concepts Analytics Lab) and Faith Matcham (Psychology) at the University of Sussex , whose work towards creating a personalised chatbot for loneliness intervention was funded by Sussex Digital Humanities Lab. Ultimately, our headline findings are that

Loneliness is generally experienced with similar intensity across demographic groups.
But the risk factors differ greatly, particularly according to age.
- Social media is discussed as a catalyst for loneliness for younger people.
- Outright social isolation is framed as a more pressing issue for older people.

For this project we explored data on loneliness collected by Mass Observation Project (MOP). In 2019 MOP issued a survey, the directive on Loneliness and Belonging (see here). The directive consisted of two parts. Firstly, participants were asked to provide five words that they associate with loneliness, e.g. despair, fear, frustration, quiet, and sad (see Figure 1). Secondly, they provided long-form narrative responses to a series of questions related to the broader topic of loneliness.

Loneliness in five words

70 Writers shared the five words they associate with loneliness. In total, 417 individual words were submitted (sentence responses excluded) with 206 different words. The top responses included terms such as isolation, sadness, alone. All 206 words expressed various aspects of affective meaning which we measured by adopting the NRC Valence, Arousal, and Dominance (NRC-VAD) Lexicon classification (Mohammed 2025). Each word is assigned a numerical value, from 0 to 1, for each of the three dimensions depending on how strongly they represent a given dimension.

Valence refers to the positive (higher score) or negative (lower score) feelings associated with each word.
Arousal relates to the intensity of the emotion, with higher scores reflecting greater intensity.
Dominance refers to the degree of control exerted by a stimulus, with higher scores corresponding to greater control. To exemplify this, Figure 1 presents the words provided by a younger female of low socioeconomic status, alongside their scores across the three dimensions.

Findings highlight remarkable consistency across demographic groups in their conceptualisation of loneliness across the dimensions of valence, arousal, and dominance. Figure 2 highlights that the average NRC-VAD scores for male and female respondents are almost identical.

Indeed, statistical analysis identified very few meaningful differences in the data set. This speaks to a remarkable homogeneity in the conceptualisation of loneliness measure by the NRC-VAD scores. The one exception to this was that on the dominance dimension there was an interaction between age and socioeconomic status. While age exhibited minimal differences among those in the lower status socioeconomic group, there was a much greater difference in the higher status group (see Figure 3). We consider age as a binary category for the purposes of this analysis, distinguishing between those who qualified for the state pension at the time of data collection (the state pension age was 65 in 2019) and those who did not.

Figure 3 shows that the effect of age on the experience of loneliness is much greater among higher status respondents, with those who are older in this category conceptualising loneliness as something that exerts a greater degree of control (0.34), relative to their younger counterparts (0.19). In particular, there is a large difference between status among younger respondents, with those of lower status (0.28) conceptualising loneliness as exerting greater dominance than their higher status counterparts (0.19).

Loneliness in long-form narratives

The longer, narrative responses to the directive discussed experiences of loneliness both on a personal level and at a broader societal level as well as speculation as to the causes of loneliness as well as potential solutions. In order to understand the ‘aboutness’ of the data we look at key terms.

The outputs of modified ‘keyword’ analysis (see our blog about modified keyword analysis here) are presented in Table 1 and the key multi-word terms in Table 2 with the responses to the directive compared against the Ententen 2020 corpus as a baseline (see here).

While a full analysis of these results is far beyond the scope of the blog here we consider one case-study, that of age.

Many of the key terms in Table 2 relate to the theme of age, e.g. young people, old age, old people, and elderly people. We have seen from the quantitative analysis of the affective meaning of the valence, arousal, and dominance that there was very little difference between age groups in the conceptualisation of loneliness (save for the interaction between socioeconomic status and age for the dominance scores). However, the longer-form responses highlight something else.

While both younger and older people are mentioned in the contexts of loneliness, the risk factors associated with these groups differ. Indeed, the discourses in which mentions of these groups appear highlight that the challenges relating to loneliness are not uniform. For example, social media was often mentioned in the context of young people:

In the news it is reported that loneliness is on the increase, particularly amongst young people. This surprises me as young people are constantly communicating with others on social media. However, perhaps seeing what looks like a perfect life on someone’s Facebook account serves to exacerbate feelings of dissatisfaction and loneliness in people whose lives are not running smoothly.
I understand that social media can cause young people to feel lonely and that other people are living a more interesting life. Unfortunately, it is full of lies but people don’t really understand that.

In contrast, discussions of older people’s loneliness were often framed in terms of isolation in more absolute terms, e.g.:

I know that there are old people today who feel lonely. Particularly following the death of their spouse.
Inevitably, as people live longer and stay in their own homes, isolation can become a serious problem. I believe the older generation can suffer considerably in this respect, particularly in rural communities where the shop and pub are now closed, the bus service has been withdrawn and children have grown up and live elsewhere.

Ultimately, using a suite of analytical tools, from sentiment analysis, to keyword analysis, to discourse analysis, enables one to garner insight into the conceptualisation of loneliness that is often missed in survey-type data. The discursive nature of this data enables lived-experiences of loneliness and its perceived risk factors to be unpacked in detail- the sort of detail that computational linguistic methods can cut through, to pick out key patterns and affective meanings. Ultimately, the findings from this report will inform the development of a chatbot that will serve as a tool to combat the loneliness crisis.

If you are interested in working with Concept Analytics Lab, please do contact us at Justyna.Robinson@sussex.ac.uk

About Us

We identify conceptual patterns and change in human thought through a combination of distant text reading and corpus linguistics techniques.

Blog

Looking back: What the Mass Observation Covid-19 diaries can teach us?

“Show me the meaning of being lonely”

How does concept-led research matter?

Identifying key content from surveys

‘We’re saying that we trust them but really we don’t’: The discursive framing of TRUST in international trade deals

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‘We’re saying that we trust them but really we don’t’: The discursive framing of TRUST in international trade deals

by Justyna A. Robinson, L. Alan Winters, Rhys Sandow, Sandra Young, Caitlin Hogan

(The updated version of this work is now published in Journal of Language and Politics. https://doi.org/10.1075/jlp.24178.rob)

Abstract

One key consequence of the UK leaving the EU (Brexit) is that it now has full responsibility for making its own international trade policy. In this context, NatCen and the Centre for Inclusive Trade Policy initiated Citizens’ Juries on the topic of trade policy. From the transcripts of these juries, we created a corpus of 317,974 words. Using corpus-assisted discourse analysis, we focus on the concept of trust in trade policy. We find that trust conferred on actors in trade policy is limited. The greatest degree of trust is conferred to experts, on account of their epistemically-elevated position. The government is broadly not trusted. Jurors wished to be consulted about trade policy decisions and be assured that they are based on sound advice, but few wished to have a role in actually making them. Our findings highlight a deficit of trust that could be remedied by greater honesty and transparency from the government.

Keywords: concept of trust, trade policy, Citizens’ Juries, corpus linguistics

1. Introduction

trust¹ is a crucial concept in citizenship, being integral to the social contract between government and citizens (see Locke 1960; Gauthier 1986). However, in a UK context, research has shown a decline in public trust in the government. For example, the Ipsos (2023) veracity index found levels of trust in politicians and government ministers to be at the lowest levels since the index began in 1983. Indeed, a report from Carnegie UK (2022) found trust to be the biggest threat to democracy, with 73% of respondents not trusting the government and 76% not trusting MPs. Winsvold et al (2024) find the basis of (dis)trust of political actors relates to their (un)predictability and intrinsic (lack of) commitment. If the government occupies one pole of (non-)trustworthiness, the literature suggests that experts are located at the opposite pole. For example, research has generally shown experts to be perceived as trustworthy (Dommett & Pearce 2019; Angelou et al. 2023), with Ipsos (2023) findings groups such as doctors, professors, engineers, and nurses to be among the most trusted groups in society. In the present article, we investigate the theme of trust in the context of UK international trade policy as it relates to a variety of actors, particularly MPs, government ministers, experts, and the public through corpus-assisted discourse analysis (see McEnery & Baker, 2015).

International trade is a major issue for the British economy. About a quarter of the UK’s demand for goods and services is met from imports and about a quarter of the demand for UK production of goods and services comes from exports. About 6.5 million jobs depend on exports. While the UK was a member of the European Union or its precursors, policy on international trade was determined in Brussels with a little input from the UK and other member governments. Brexit brought full responsibility for UK trade policy back home to a government ill-equipped to discharge it, not least because it had little idea about attitudes to trade among the public.

In the years shortly after Brexit came into effect (2021) the UK had rolled over 30 trade agreements that it had been party to under the EU, agreed new terms for trade with the EU and signed new agreements with, Australia and New Zealand and with the Comprehensive and Progressive Trans-Pacific Partnership (CPTPP) with 11 Pacific nations. The 30 roll-overs (imperfectly) preserved the trading conditions the UK had under the EU, the agreement with the EU offered vastly inferior trading conditions to those which it had as a member, and official estimates suggested that the economic benefits of the new trade agreements were trivial – see Winters (2024).

This was the context in which the Centre for Inclusive Trade Policy (hereafter, CITP)² was created (funded by the Economic and Social Research Council) and in which one of the Centre’s early objectives was to find out how the public thought about trade policy – its reasoning, the criteria by which it judged policy and policymaking and how it reacted to specific trade-offs. (Trade policy always entails trade-offs – more of A and less of B and/or more for X and less for Y.)

The chosen instrument was a series of five Citizens’ Juries in which small groups were informed about, discussed and in some cases made mock decisions about trade policy questions. The recordings of these juries’ final discussions provide the raw material for this analysis, in which we look specifically at the questions of whom the public trusts to inform decisions and whom they trust to make them. A few more details are provided in Section 2 and a good deal more in the documents at CITP (2023).

The concept of trust is explored through corpus-assisted discourse analysis, using both quantitative linguistic data as well as thematic analysis of narratives that illustrate the discourses of trust among the Citizen Jurors (hereafter, CJs). In particular, the current analysis serves to answer the research question –- to what extent is trust conferred on actors in UK trade deals? We consider who is trusted and who is not, and what are the underlying motivations for these assertions. The main characteristics of the concept of trust that arise from the CJs’ conversations are:

CJs place very limited trust in political actors
CJs recognise that trust is critical to political processes
CJs feel that there is a lack of options in who to trust
CJs express a relatively high degree of trust in experts
CJs’ opinion on trusting the public is divided
CJs make a distinction between actors they trust to inform and to decide on trade deals

In Section 2 we discuss corpus-assisted discourse analysis as a method of analysing CJ conversations. In Section 3 we present findings which start with an observation that jurors place very limited trust overall in the process of decision-making with regards to trade deals. We then report on the relatively high levels of trust CJs afford to experts, and the limited trust they confer on the public. Specifically, we note the distinction that CJs made between informing the decision-making process and actually making decisions regarding trade policy.

2. Method

The data interrogated in this report come from the transcripts of the final day of the CITP’s Citizens’ Juries on UK Trade Policy – ‘Trade-Offs in Trade Policy’. These were conducted by the National Centre for Social Research’s Centre for Deliberative Research³ (hereafter, NatCen) in Belfast, Bridgend, Doncaster, Paisley, and Reading, between 11^th January and 4^th February 2023. The aim of the juries was (i) to uncover how UK residents felt about the trade-offs that any act of international trade policy entails, but only after they had been given some (carefully balanced) information about the issues at stake and (ii) more importantly, to understand how they reasoned about the trade-offs as they came to their views. One focus of the latter was whom they trusted to inform the decision (and the public) and whom they trusted to take the decisions.

Each jury was of around 20 people (with no attrition – perhaps because jurors were remunerated) and representative of its local area. Each met five times: four times virtually for 2.5 hours each and once face-to-face in the final all-day session. At each meeting there were some plenary sessions (of the whole of one jury), but most deliberations took place in groups of about six with a facilitator. Each on-line session dealt with a different trade policy area, i.e.

The impact of UK trade policy on the rest of the world
Balancing trade between territories and sectors of the economy
Privacy and international data transfer
Food trade and the environment

CITP researchers made carefully-balanced, impartial presentations on aspects of these but then withdrew for the discussions. The face-to-face meeting had one session on each of the four issues based around a specific question, plus an introduction and a wrap-up session. Face-to-face the format was for NatCen to present on an issue, for deliberations to occur and then a vote to be held on which participants briefly recorded the main reason for their vote and then discussed how they voted. We then modified the scenario a little and the process was repeated. The modification approach was designed to reveal the jurors’ trade-offs more clearly. Details of the process are laid out in detail in the documents at CITP (2023).

The discussions from the final meeting were audio-recorded and fully transcribed by a professional transcription service. The recordings were not perfect, and the transcription noted inaudible segments wherever they occurred. The data were annotated for the speaker type, i.e. juror or interviewer, male or female (inferred from the audio recordings), the scenario that was being discussed, the location of the Jury, and the name of the facilitator.⁴

The overall CJs dataset (corpus) consists of 317,974 words and 396,380 tokens (token are words plus punctuation). Of these tokens, 139,527 (35.2%) were produced by male jurors, 157,972 (39.9%) by female jurors and the remainder (24.9%) to facilitators. Thus, the overall data is relatively well-balanced in terms of gender (it was perfectly gender-balanced in terms of membership.). Across the five locations, the distribution of tokens is also relatively even. The highest number of tokens come from Belfast (23.9% of total tokens in the corpus) while the joint fewest come from Bridgend and Paisley (18.5%), see Figure 1.

In order to investigate how the jurors conceptualise and construct the concept of TRUST in the contexts of trade deals, we employ methods associated with corpus-assisted discourse studies (CADS, see Partington 2004). This methodology combines the quantitative power of corpus linguistics, in which large electronic collections of text may be analysed and common trends identified, with the qualitative perspective of discourse analysis. Corpus linguistics, including CADS, can be done via a range of software tools, including Sketch Engine (Kilgariff et al. 2004; Kilgariff et al. 2014), which is used in this study. This tool calculates, amongst other outputs, frequencies of words and word clusters (known as keywords when compared to a reference corpus⁵ to detect statistically significant frequencies within a given text), collocations (cooccurrences of a target word with others) and concordance lines (sections of the text itself which facilitate more qualitative analysis). In particular, Sketch Engine was selected for this study due to the utility of its Word Sketch feature, in which a range of grammatical relations (such as modification, verbs with a search term as their object/subject, prepositional phrases, adjectival predication, etc) can be displayed at once. We term these visualisations behavioural profiles. The behavioural profile allows for streamlined analysis of how terms behave or function in the text, the constructions in which they frequently occur, and how they may operate within circulating discourses. The behavioural profiles that we present are not comprehensive of all possible constructions a word appears in. This is so that the visualisations remain readable, as the complete versions contain hundreds of data points, and that the information that is pertinent to our discussion is retained and foregrounded. CADS employs a mixture of these statistical methods with close discourse analysis to identify quantitative linguistic patterns as well as a more qualitative perspective which adds context and detail to these empirical results. By applying these methods to the analysis of the concept of trust we identify people and entities CJs place trust in and what conditions are imposed on that trust within the discourses of the CJs. While the current analysis of trust primarily centres on the word trust as both a noun and a verb (as well as words with the trust stem, e.g. trustworthy) this is also supplemented by less frequent near-synonymous constructions involving verbs such as to rely on and to believe, or where trust is implicit in the context of discourse. This focus on trust is motivated by the distinctiveness of constructions containing trust in the CJ corpus, which is further outlined in the results section.

In analysing the discourse of CJs, the primary way we approach the concept of trust is through the notion of stance (Du Bois 2007; Jaffe 2009). We consider two types of stance throughout the current analysis. Affective stance refers to the orientation towards the topic of discourse, that is, the stance object, such as positive or negative, see Eckert (2019), while epistemic stance refers to an individual’s certainty in the content of their proposition (see Kiesling 2009). While there are a variety of ways that stance is indexed through language (for review, see Kiesling 2022), our focus is on discourse. Specifically, we consider how the use of particular words or expressions provide insight into attitudes towards trust in the context of trade deals. These expressions include heavily value-laden words (e.g. love, struggle, bad, good) as well as those that are more functional but speak to permissibility and obligation, such as deontic modal verbs (e.g. should, need), and the use of discourse strategies such as hedging (e.g. ‘I think…’ ‘maybe..’).

The final note in this section outlines transcription and presentation conventions of the data and addresses some of the challenges faced by working with natural spoken conversations. Quotations used in the paper are accompanied by the gender of the speaker and the location of the CJ (it is often not possible to identify the individual speaking in large groups). Where more than one juror is quoted, we refer to this as ‘various (speakers), [location]’. Where speech is produced by a facilitator this is represented in italic font. While the facilitator text is not the subject of our analysis, it often provides important context in which the discourses of the jurors can be interpreted. It is important to note that given that in spoken interactional discourse, such as the CJs, much of the meaning being expressed is extra-linguistic and, therefore, is not captured through transcription. There are also many examples of incomplete utterances as well as anaphoric references for which the anaphor is not clear. We include examples that we feel are relatively high in clarity and are not especially difficult for the reader to parse.

3. Results

Both quantitative linguistic analysis and close reading of the texts highlight the concept of trust as being of widespread yet heterogenous in CJs’ conversations. For example, the word trust is distinctive within the CJ corpus. This is highlighted by several measures. In comparison with the baseline corpus, the word⁶trust appears within three of the top-ten three- and four-grams (i.e. strings of three or four words). The word trust itself is analysed at both verb (375 occurrences) and noun (103), as well as words which include trust in the stem (trust *), such as trusting (16) and trustworthy (2). Trust* is a relatively frequent stem in CJs corpus as it accounts for 0.12% of the corpus.⁷

The exploration of the concept of trust in CJs corpus starts with an overview of the use of the verb to trust in the texts. A behavioural profile for the verb trust can be seen in Figure 2.⁸ When interpreting behavioural profiles, the different colours correspond to the different grammatical relations with trust, the size of the circle represents the raw frequency of the collocation between the word and trust, and the closer the position to the centre of the circle, the stronger the collocation between that word and trust (calculated by logDice score). The segments represent different grammatical relations, e.g. grammatical objects of trust (e.g. trust people) and modifiers of trust (e.g. really trust).

The results presented in Section 3 are mainly led by findings in Figure 2. On the basis of that analysis we identify salient discursive frames within which CJs place the concept of trust. Figure 2, shows that trust+not is typical of CJs’ conversations about trade deals. Thus, we discuss the lack of trust, and who is not trusted in Section 3.1. Presence of collocates expert, scientist in Figure 2. leads to the analysis of the trust afforded to experts in section 3.2, as well as trust (and lack thereof) in the public in Section 3.3. Figure 2 shows that two of the top infinitive objects of the verb to trust are to decide and to inform. Thus in Section 3.4 we explore how different types of actors are trusted to have deciding or informing functions within trade policy. We report that experts are trusted to consult and government is trusted (reluctantly) to make decisions.

3.1 The lack of trust

The most frequent collocation in Figure 2, not + trust, with 54 hits across the CJs corpus, highlights the lack of trust afforded by the jurors, with a small number of participants admitting they don’t trust anyone in the context of trade deals:

I can’t trust anyone (Female, Bridgend)
I don’t trust anybody, to be honest (Female, Reading)

However, this lack of trust is not uniform, and there are some groups of people and institutions who feature in the context of not + trust more than others. This is evidenced by the grammatical objects of the not + trust construction presented in Figure 3.

This lack of trust is principally directed at political actors seen in the collocations between not + trust and government (n=14); politician (n=2); MP (n=1). For example:

Who do I trust to inform? Well, I don’t trust the government […]They are what they call the public school mentality, isn’t it? They haven’t got a clue really. (Female, Bridgend)
I don’t trust any of them, to be honest. We can go back to the: I don’t trust politicians full stop – which is sad that I feel that. Aye. (Female, Paisley)
I don’t trust the MPs to [negotiate trade deals] because they will have a vested interest. (Male, Belfast)

The examples above exemplify some of the CJs’ attitudes pertaining to the government. For example, ‘[the government] haven’t a clue really’ reveals a negative affective stance towards the government and their perceived capabilities. Strong epistemic stances (see Section 2) are also demonstrated through the lack of hedging, e.g. ‘I think’, ‘maybe’, or ‘sort of’, while unhedged comments, such as ‘I don’t trust politicians full stop’, reveal a strongly held belief.

Despite this lack of trust in political actors, a number of jurors do comment that they reluctantly trust the government. That is, many have resigned themselves to trust the government in the perceived absence of an alternative:

I have no choice but to trust the government. We were going to say, like, politicians, it’s like a bad word these days, but we’ve no option but to trust the government in international trade committees, that they’re speaking to people and know what they’re talking about. (Male, Belfast)
Would I trust local government? They’re the only place you can go to. They’ve got more connection, the local government. Yes. It’s almost like choosing your form of execution, isn’t it …? Yes. What do you want to do; electric chair or a bullet? (Various speakers, Bridgend)

It is often unclear from CJs’ conversations whether it is political actors who are untrustworthy in principle or if it is the specific political actors of the day that are being objected to. While the lack of trust in these actors is evident, many jurors resign themselves to the necessity of politicians in the context of trade deals and that there are few alternatives so their trust towards these political actors is given begrudgingly.

3.2 Experts

The actors who are seen more favourably by CJs in the context of trade deals are experts. A number of collocations between trust and expert occur (see Figure 2). As expert is a semantically broad term, we unpack what/who the jurors refer to when they speak of experts. This can be identified by the behaviour profile for expert, as shown in Figure 4.

Figure 4 displays the verbs used with expert as the grammatical object, nouns modified by expert, the modifiers of expert, and the nouns in conjunction with expert. Collectively these serve to highlight the sorts of domains of expertise that jurors referred to. In particular, academic roles collocate strongly with expert e.g. researcher (as both a modifier of expert and in conjunction with expert), university, and the related term scientist (as both a noun modified by expert and in conjunction with expert). Other specific fields such as business, medical, legal, and economist are also mentioned. Additionally, the more generic subject expert is mentioned as well as appropriate and relevant, that is, an expert in whatever is related to the specifics of a particular deal.

The trust afforded by CJs to these experts is clearly expressed, e.g.:

trust the experts of the trades, so example agriculture would be farmers and so on. (Female, Bridgend)
We really trust the scientists on this question [of food standards] (Female, Paisley)

While the examples above highlight the industries that jurors associate with experts in the context of trade deals (e.g. medical, legal), other collocates in Figure 4 speak to the types of traits that are associated with experts, particularly the modifiers independent and neutral which are qualities that the jurors valued. For example:

[I trust] neutral experts [to inform trade policy] […] I said the other MPs, so Labour, Conservative, whatever, with the vested interest and baggage and maybe backhanders, whereas experts, we hope are above that (Male, Paisley)

The independence that the jurors associated with experts was also associated with international bodies, for example:

Someone like the World Health Organization has a blanket view of what’s good and what’s not as opposed to us deciding that. You’re saying the WHO because they’re independent. Yes, they should be. Or an equivalent independent body. (Various, Reading)

These examples highlight a positive affective stance towards independent international bodies and their perceived capacity to prioritise the public good, rather than particular interests.

Close reading of sentences containing terms for experts and terms which are typically used in conjunction with terms for experts (see Figure 4) also reveals a similarly positive affective stance in terms of advocating for the role of experts in trade strategy, in particular in the context of the perceived elevated knowledge base of experts, relative to politicians, e.g.:

It’s like the experts, the ones that are not in it for financial gain […] so they’re the knowledge. An MP might not necessarily have the knowledge. (Female, Doncaster)
Let the scientists meet and agree the best decision. (Male, Belfast)

Jurors also mention that the government would be trusted to a greater extent if it was clear that they had consulted experts:

Like we’d have more confidence if we knew that they [the government]’ve spoken to the experts in the field or spoken to whoever we felt should be relevant (Female, Reading)

Thus, for some jurors, the trust in experts can serve to offset their lack of trust in the government.

Trade unions, or their representatives, are sometimes framed as a specific type of expert who should be consulted on trade deals, although not without dissenters. For example:

I’d also trust trade unions to have a part in it, because they obviously act on behalf of their members who are the general public. (Female, Belfast)
I think maybe a trade union, they will think for their own interest so I am not sure about the union. (Female, Bridgend)

Another way in which we identify general sentiment is by analysing the verbs that occur in the context of a given noun (see, e.g. Biber 2006). For example, through the analysis of the verbs that are used with expert, we can provide additional insight into how the jurors perceive experts (see Figure 4). The strongest collocate of verbs with expert as object is need. This highlights the ways in which the consultation of experts is framed as imperative:

We need experts who are qualified to comment on world population, world growth, who is dying of hunger (Male, Paisley)
We need experts to decide whether this is […] worth the risk (Male, Paisley)

Ultimately, of all of the groups discussed in relation to trade deals, jurors frame experts most positively. They expressed trust in experts in the context of informing the government. In particular, jurors favour experts due to their perceived independence and epistemically leading position.

3.3 Public

Another group regularly discussed in the context of trust was the public (see Figure 2). The perception of the public in relation to trust is complex. On the one hand, CJs see the public as incapable of having sufficient knowledge to be trusted around policy decisions, for example:

You don’t want to trust the general public to make the decision because we’re not informed enough, or we don’t know enough about it to be able to make an informed decision. (Female, Belfast)
We are slightly more informed, but the rest of the general public would probably know very little (Female, Belfast)

Such attitudes, which speak to the perception of the limited epistemic position of the public, are also evident in the behavioural profile for the noun public (see Figure 5).

The collocates of public, such as idiot, child, and stupid (see Figure 5) exemplify the public’s perceived naivety and lack of knowledge:

So we put business owners from the specialist sector, and then we originally had public, and then we agreed that the public are idiots (Female, Paisley)
Don’t ask the public. The public are stupid (Female, Bridgend)

While the collocates educate and inform do occur in Figure 5, these are typically used in phrases in which they are negated, highlighting the way that the public are not educated or informed, with respect to trade strategy. For example:

Are most of the public educated enough to make decisions like this? We’re not, are we, I don’t think (Male, Doncaster)
I don’t think the public are informed enough to be involved in making big decisions like this. I think it needs to be left to the experts (Male, Belfast)

On the other hand, the public are conceptualised as being close(r) (adjective predicates in Figure 5) to relevant issues, and, as such, have a right to have a voice, for example:

I was going to say, I don’t think many people trust the government, do they? Yes, I think also the people, the public are closer to the issues, have personal experience of issues that have affected them (Female, Belfast)

Many jurors highlight the value of consulting the public. However, as the CJs do not think that the public has sufficient knowledge of the intricacies of trade, they typically do not advocate for public involvement in making decisions that directly affect trade policy. This highlights a broader distinction between which actors were discussed in reference to those who were trusted to decide vs inform on trade policy.

3.4 Informing vs deciding

While attitudes towards different types of actors vary greatly, CJs also have a varied opinions on the sorts of responsibilities each type of actor should be tasked with. The jurors make a distinction between the actors that they feel should be involved in the consulting stage of trade deals and the process of decision making. This distinction is highlighted in the following example:

So, yes, who else should inform? Who…? Yes, we kind of said that. We said the professors, the people who know what they’re talking about, the people who’ve studied this, and so we said they should make the decisions. We said they should inform. Inform, sorry, not make decisions. They’re the ones who should inform the government. Yes, so the decision-makers should be really listening to […] Because they’re the ones who inform researchers. It’s like the experts, the ones that are not in it for financial gain, the ones that gain something, so they’re the knowledge. An MP might not necessarily have the knowledge. Yes, they can make the decision, or they can put something forward, but they don’t know the knowledge. They’ve not studied it, so I think they have to listen to experts and researchers, people that know (Various, Doncaster)

Motivated by findings presented on Figure 2, we focus on the decision-making processes in relation to trade deals which are represented by a set of verbs inform/consult and decide (see Figure 2). We generate a visualisation of the collocates that occur as grammatical subjects of verbs to inform and to decide (Figure 6)⁹. Terms that appear closer to the left of Figure 6. collocate more strongly with to inform while those that appear on the right have a stronger collocation with to decide, while the size of the text relates to the raw frequency of the collocation (e.g. people has a higher raw frequency than Ireland).

Figure 6 shows that scientist and farmers, which are types of experts, are discussed in the context of informing trade policy. Relatedly, Figure 7 presents a comparative behavioural profile for decide and consult, which is near-synonymous to inform. It shows that public and people, as well as expert collocate more strongly with consult than decide. Thus, the semantic fields of the public and experts are more strongly collocated with inform/consult.

The theme of government is much more strongly associated with decide, such as MP, government, and minister (see Figure 6). Further analysis of the concordances demonstrates the ways in which the jurors framed (members of) the government as those who should be making decisions:

Also we’ve come out with the UK Government making the decision about any trade agreement. Are they still the best placed to do this, or are there other groups that you think should decide on an agreement like this? I think so. I think that’s what they’re there for, isn’t it; they’re the ones that make the decisions but they need to make informed decisions. (Female, Reading)
Yes, I think that was the point you were making earlier on; that that’s their job and that’s what they should be getting on with. Yes. … I would hope it’s – nobody else should be making decisions. Governments, they are elected and they can be dealing with it. Yes, because it’s the diplomatic system we have. I would just hope – my hope would be that their decisions are informed by consulting experts; that’s what we were discussing. (Male, Belfast)

One comment suggests that the government should simply enact the decisions of the public and experts:

Who do you think you trust most to make these decisions? I don’t think one; I think it should be a combination of the public and the government. Yes. With the government initially with the public on a scale of, I reckon, about 70-30 per cent, so the public should be able to make 70 per cent of the choices, with 30 per cent coming from the experts – not the government – and then the government enforcing the decision. (Various speakers, Bridgend)

Jurors suggest that while experts should play an important role in the process, it is the role of government to ultimately make decisions:

So, who do people feel like should be making these decisions about which jobs we might be creating, who should be winning or losing from trade? I think it should be the government – like we discussed in the last […] but with people feeding in, whether it be unions or the agricultural […] What do they have? Do they have some sort of union? I don’t know. Feeding into them and giving them the information, but we can’t have different sets of people making different decisions. Yes. In relation to trade policy. It’d be all over the place. It’s got to be Central Government I think, making the decision. (Male, Bridgend)
I think government should always be making the ultimate decision because they are elected to do so. On the advice of the experts. And us. A wee bit. Select few, yes. (Male, Belfast)

The collocations of decide vs inform highlight the distinct processes in the development of trade deals. CJs provide recommendations and have clear ideas on obligations of various actors through a repeated use of deontic need or should. While the public and experts are more likely to be discussed in the context of informing and consulting on trade deals, it is the government who should be ultimately responsible for making decisions. However, a number of jury members, particularly in Reading, were not content with this arrangement, highlighting a desire for an entirely new and bespoke assemblage of people to be responsible for trade deals.

4. Discussion

The CJ data speaks to the limited trust conferred on politicians and political processes. The government was not trusted in absolute terms but were begrudgingly trusted to be responsible for ultimately signing trade deals. Using Cairney & Wellstead’s (2021: 2) typology of trust, we can think of this as ‘trust as necessary to society’, that is, while the trust is not enthusiastically given to the government, it is perceived to be essential for the running of the state. However, the government are not trusted in terms of their reliability, competence, degree of selflessness, or shared identity or values (Cairney & Wellstead 2021).

Experts, despite frequent lack of specification as to who experts actually are, are evaluated positively according to a variety of Cairney & Wellstead’s (2021) trust categories. In particular, their input in informing trade deals was viewed as necessary to society. They were also evaluated positively in terms of competence, (relative) selflessness, reliability, and performance. There are no categories in relation to which experts were routinely explicitly negatively evaluated. Thus, while then then Secretary of State for Justice, Lord Chancellor, Michael Gove famously claimed that the public have ‘had enough of experts’, this is diametrically opposed to the evidence from the citizens’ juries as well as other sources such as Ipsos (2023). Overall, the epistemic trust for experts is high, that is, they are perceived to have accurate and relevant information that can serve to benefit the UK’s interests in trade deals.

Applying Cairney & Wellstead’s (2021) trust typology to the public, they are not valorised positively in terms of competence. In particular, they are not thought to have the specific knowledge base required for complex geopolitics and economic analysis. However, they are perceived more positively in terms of having shared identities or values and mutual self-interest. That is, they are perceived to be trustworthy in the sense of a willingness to do the right thing, though not necessarily have the competence to carry this out independently, without the involvement of the government and experts. This nuanced view of public involvement in decision making has also been seen in research looking at another complex decision-making area, health (Litva et al. 2002). Employing Arnstein’s (1969) ladder of citizen participation, the responses typically call for a partnership, without extending this participation to delegated power or citizen control.

While participants did not provide detailed rationales for the lack of trust, some did mention Brexit as a contributory factor for their scepticism of government and perceived vested interests, e.g.:

I can’t trust anyone. Recently, because of Brexit as well, the promises which were made… Promises, promises, promises. (Female, Bridgend)
Brexit were a game-changer wasn’t it? It was, and I also feel very manipulated by Brexit, by the media. (Male, Doncaster)

As the need for UK-specific trade deals is a direct consequence of Brexit, the spectre of Brexit looms large in the CJs. However, the scenarios, presentations and notes for facilitators all sought not to avoid re-igniting Brexit controversies, partly to try to maintain a harmonious atmosphere but also because we wished to reach beyond Brexit to more fundamental building blocks of attitudes to international trade. Thus, the relative scarcity of ‘Brexit’ in these conversations is not an indication of its lack of salience.

Conversely, the levels of trust conferred on experts seems to have been boosted by their role in the Covid-19 pandemic:

Bodies like the IMF, World Health Organization during COVID, those international organisations, when they don’t have a single country it’s just like, ‘I’ve got to get elected in the next three years’. These organisations are less relying on elections coming up to win; it’s just like a general benefit of people. (Male, Bridgend)
Well, in COVID we relied on the experts. Yes. For daily briefings and everything, it was the experts you listened to. Yes, if an expert was like, do you know what? This would work out better for you’ and then the MPs is like ‘no, you’re wrong’, I’d be like […] I don’t believe in the government or MPs. (Various, Bridgend)

Thus, the public are using recent events as frames of reference when deciding with whom to bestow their trust. While the Brexit campaign generally served to diminish levels of trust in politicians, the role of experts, and their visibility, in the Covid-19 pandemic has led to their stock rising.¹¹

5. Conclusion

The over-arching finding from the corpus-assisted discourse analysis of the citizens’ juries is that trust pertaining to actors involved in trade deals is severely limited. In particular, the role of politicians was viewed least favourably, while more positive affective stances were apparent in the context of experts. The perceived lack of transparency, the suspicions about vested interests, and the general lack of awareness of the day-to-day life of the public and their wants and needs meant that the levels of trust afforded to political actors was limited. Trust in politicians has never been high (Clements and King 2023) but it is worth remembering that in early 2023, when the juries were held, the British public had noticed that Brexit was not the overt success that had been promised and that in the previous seven months one Prime Minister had resigned in disgrace and the next had precipitated such an economic crisis that she had to resign after just seven weeks. Thus, one might hope for a little more trust in future.

It is also important to recall that many jurors did, begrudgingly, want ultimate accountability for trade deals to rest with the government and so believe that the government should make final decisions on trade. Jurors believed widely that the public as well as experts should be informed, and in some cases consulted, about trade-policy issues. However, there was little enthusiasm for them to have a decisive role, not least because they felt insufficiently informed about such a complex issue. Their stated trust in experts of various kinds reinforces the latter view.

The Citizen Jurors’ views on trust suggest a considerable institutional deficit in the UK treatment of international trade policy, which is, after all, a major component of overall economic policy. Future governments should speak more frequently and more honestly about the questions of trade policy; they, along with the public and the media, need to accept that given the nature of the trade-offs involved almost no policy will command universal support. Rather, the trick needs to be that the country’s overall stance on trade delivers benefits to nearly everyone and that where it cannot, provisions are made to ease any burdens created. In concrete terms, partly in response to these Citizens’ Juries, the Centre for Inclusive Trade Policy has advocated:

greatly strengthening Parliamentary scrutiny of trade agreements and trade policy (Hestermeyer and Horne, 2024, Winters 2024)
better engagement with the UK’s devolved administrations and their populations on trade (Petetin et al, 2023), and
related to suggestions from some jurors, reforming the UK Board of Trade to provide independent expert analysis and advice on trade policy to the government, Parliament and the public (Henig & Winters 2024, Winters 2024).

Footnotes

Small caps indicate the concept, that is, the idea of trust, and italics are used when referring to the word trust metalinguistically. ↩︎
https://citp.ac.uk/ ↩︎
https://natcen.ac.uk/centres/centre-for-deliberation ↩︎
In total there were 90 transcript documents: 5 juries x 3 discussion groups x 6 discussions (4 scenarios plus intro and wrap-up). ↩︎
We use the Spoken British National Corpus (2014, Love et al. 2017) as our reference corpus. This is a 10-million-word corpus represents spoken English in Britain. ↩︎
This n-gram search does not distinguish between trust as a noun or a verb. ↩︎
This contrasts with 0.0013% of the baseline corpus. ↩︎
We focus on the verbal rather than the nominal form here for two reasons. The first reason is quantitative. There are nearly four times more tokens of the verbal form (375 against 103). Secondly, a collocation analysis of verbs enables clearer insight into who trust is being conferred on by the jurors, thus the verbal analysis is more felicitous in order to understand the application of trust in the CJs. ↩︎
In Sketch Engine, it is not possible to search for both inform and consult simultaneously in comparison with decide, thus we need to conduct the relevant searches sequentially. ↩︎
The decide side of the figure refers to both government and Government: the former is generic while the latter refers to a specific government (almost always the UK’s). ↩︎
Winters (2020) contrasts the official attitudes towards expertise in Brexit and Covid-19 policymaking. ↩︎

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About Us

We identify conceptual patterns and change in human thought through a combination of distant text reading and corpus linguistics techniques.

Conceptual variation: Gendered differences in the lexicalisation of the concept of COMMODITY in environmental narratives

Abstract

1. Introduction

2. The Concept and Lexicalization

3. Data

4. Method

5. Results and Analysis

5.1. Semantics of the MORE corpus: Keysenses and keyconcepts

5.2. Gendered variation in the MORE corpus: Keyconcepts and lexicalization patterns

6. Summary and Conclusions

Footnotes

References

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How language reveals different faces of loneliness

Loneliness in five words

Loneliness in long-form narratives

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‘We’re saying that we trust them but really we don’t’: The discursive framing of TRUST in international trade deals

Abstract

1. Introduction

2. Method

3. Results

3.1 The lack of trust

3.2 Experts

3.3 Public

3.4 Informing vs deciding

4. Discussion

5. Conclusion

Footnotes

References

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