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

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

by Sandra Young

In this blog post (published 24 March 2025 by the Mass Observation Archive), Concept Analytics Lab shares how researchers can explore  the Covid-19 diaries collected during the pandemic in order to better understand how everyday people experienced that time.

When researchers compared pandemic diaries to ones from the previous decade (2010–2019), a list of key terms included words like lockdown, Zoom, furlough, social distancing, and home schooling. These highlight not just what people were dealing with, but how they were trying to make sense of a completely new and strange situation. By looking at how words like Zoom were used in context, such as with work meetings, online classes, or even quizzes and parties, we get a better idea of what daily life actually looked like.

Some terms show how regular activities suddenly became more important. Things like daily walks or video calls stood out in a time when social lives moved online. Phrases such as strange times and normal people reveal how diarists were navigating the weirdness of life under lockdown.

The blog also introduces ConceptCruncher, a tool developed at the Concept Analytics Lab that maps out the main themes in the 2020 diaries compared to earlier years (see Figure 1).

All in all, the MO Covid-19 collection offers a powerful look at how people lived through the pandemic, and distant reading tools help researchers make sense of this rich and complex data. See here to access the full blog post.

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Effective Date: 14 May 2025

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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

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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

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 11th January and 4th 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.

Figure 1: Distribution of tokens in the CJs corpus for each location
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).
Figure 2: The behavioural profile for the verb to 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:
  1. I can’t trust anyone (Female, Bridgend)
  2. 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.

Figure 3: Objects of not+trust in the CJs corpus.

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:

  1. 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)
  2. 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)
  3. 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:

  1. 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)
  2. 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: The behavioural profile for expert

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.:

  1. trust the experts of the trades, so example agriculture would be farmers and so on.    (Female, Bridgend)
  2. 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:

  1. [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:

  1. 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.:

  1. 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)
  2. 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:

  1. 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:

  1. 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)
  2. 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:

  1. We need experts who are qualified to comment on world population, world growth, who is dying of hunger (Male, Paisley)
  2. 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:

  1. 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)
  2. 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).

Figure 5: The behavioural profile for public

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

  1. 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)
  2. 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:

  1. Are most of the public educated enough to make decisions like this? We’re not, are we, I don’t think (Male, Doncaster)
  2. 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:

  1. 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:

  1. 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: The comparative behavioural profile for to inform and to decide (subject position).

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.

Figure 7: The comparative behavioural profile for to consult and to decide (subject position).

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:

  1. 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)
  2. 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:

  1. 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:

  1. 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)
  2. 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.:

  1. I can’t trust anyone.  Recently, because of Brexit as well, the promises which were made…  Promises, promises, promises.  (Female, Bridgend)
  2. 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:

  1. 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)
  2. 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. ↩︎

References

Angelou, Angelos., Stella Ladi, Dimitra Panagiotatou, & Vasiliki Tsagkroni. 2023. Paths to trust: Explaining citizens’ trust to experts and evidence-informed policymaking during the COVID-19 pandemic. Public Administration, Advance Online Publication.

 

Arnstein, Sherry R. 1969. A ladder of citizen participation. Journal of the American Institute of Planners, 35 (4), 216-224.

 

Biber, Douglas. 2006. Stance in spoken and written university registers. Journal of English for Academic Purposes, 5, 97–116.

 

Cairney, Paul. & Adam Wellstead. 2021. Covid-19: Effective policymaking depends on trust in experts, politicians and the public. Policy Design and Practice, 4 (1), 1–14.

 

CITP (2023) Research into public attitudes to trade, CITP, University of Sussex,  https://citp.ac.uk/public-attitudes-to-trade

 

Clements, Michael and Laura King 2023. Trust in politicians reaches its lowest score in 40 years, IPSOS, 14th December 2023, https://www.ipsos.com/en-uk/ipsos-trust-in-professions-veracity-index-2023

 

Dommett, Katharine. & Warren Pearce. 2019. What do we know about public attitudes towards experts? Reviewing survey data in the United Kingdom and European Union. Public Understanding of Science, 28 (6), 669-678.

 

Du Bois, John W. 2007. The stance triangle. In Robert Englebretson (Ed.), Stancetaking in Discourse, 139–182. Amsterdam: Benjamins.

 

Eckert, Penelope. 2019. The limits of social meaning: Social indexicality, variation, and the cline of interiority. Language, 95 (4), 751–776.

 

Gauthier, David. 1987. Morals by Agreement. Oxford: Oxford University Press.

 

Henig, David and L Alan Winters (2024). ‘Restructuring the Board of Trade for the Twenty-first Century’. Centre for Inclusive Trade Policy Working Paper 014, https://citp.ac.uk/publications/restructuring-the-board-of-trade-for-the-twenty-first-century

 

Hestermeyer, Holger and Alex Horne. 2024. Treaty Scrutiny: The Role of Parliament in UK Trade Agreements, Briefing Paper 9, Centre for Inclusive Trade Policy, https://citp.ac.uk/publications/treaty-scrutiny-the-role-of-parliament-in-uk-trade-agreements

 

Jaffe, Alexandra. (Ed.). 2009. Stance: Sociolinguistic Perspectives. Oxford: Oxford University Press

 

Kiesling, Scott F. 2009. Style as stance. In Alexandra Jaffe (Ed.), Stance: Sociolinguistic Perspectives, 171–194. Oxford: Oxford University Press.

 

Kiesling, Scott F. 2022. Stance and stancetaking. Annual Review of Linguistics, 8, 409-426.

 

Kilgarriff, Adam., Pavel Rychlý, Pavel Smrž, David Tugwell. 2004. The Sketch Engine. Proceedings of the 11th EURALEX International Congress, 105-116.

 

Kilgarriff, Adam., Vít Baisa, Jan Bušta, Miloš Jakubíček, Vojtěch Kovář, Jan Michelfeit, Pavel Rychlý, and Vít Suchomel. 2014. The Sketch Engine: Ten years on. Lexicography, 1: 7-36.

 

Litva, Andrea., Joanna Coast, Jenny Donovan, John Eyles, Michael Shepherd, Jo Tacchi, Julia Abelson, Kieran Morgan. 2002. ‘The public is too subjective’: public involvement at different levels of health-care decision making. Soc Sci Med, 54(12), 1825-37.

 

Love, Robbie., Claire Dembry, Andrew Hardie, Vaclav Brezina, & Tony McEnery. 2017. The Spoken BNC2014: Designing and building a spoken corpus of everyday conversations. International Journal of Corpus Linguistics, 22(3), 319-344.

 

Locke, John. 1960. Two Treatises of Government. Ed. Peter Laslett. Cambridge: Cambridge University Press.

 

Partington, Alan. 2004. Corpora and discourse: A most congruous beast. In Alan Partington, John Morley, and Louann Haarman (eds.), Corpora and Discourse, Bern: Peter Lang, 9-18.

 

Petetin, Ludivine., Charles Whitmore, and Aileen Burmeister (2023) ‘Addressing barriers for Welsh institutions and civil society to contribute to UK trade policy’, CITP Briefing Paper 6, https://citp.ac.uk/publications/addressing-barriers-for-welsh-institutions-and-civil-society-to-contribute-to-uk-trade-policy

 

Winsvold, Marte., Atle Haugsgjerd, Jo Sagile, & Signe Bock Segaard. 2024. What makes people trust or distrust politicians? Insights from open-ended survey questions. West European Politics, 47 (4),759–783.

 

Winters, L. Alan (2020) ‘Brexit and Covid: Experts – who needs ‘em?’, The UK in a Changing Europe,   https://ukandeu.ac.uk/brexit-and-covid-experts-who-needs-em/

 

Winters, L Alan (2024) ‘How do we make trade policy in Britain? How should we?’ Centre for Inclusive Trade Policy Working Paper 011, https://citp.ac.uk/publications/how-do-we-make-trade-policy-in-britain-how-should-we

 

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

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How do concepts matter for language in the human-machine era?

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How do concepts matter for language in the human-machine era?

by Justyna A. Robinson and Sandra Young

Questions of conceptual content in language are important to applications relying on human-machine models of language. In this context, Concept Analytics Lab has been awarded funding from the COST (European Cooperation in Science and Technology) Action Network initiative. The aim of the grant was to explore synergies and ideas through events organised by LITHME (Language in the Human Machine Era) research programme, such as

What is LITHME?

LITHME (Language in the Human Machine Era) was launched in 2020 as an EU COST Action network. The aim of LITHME is to explore questions relating to the interface between language and technology in what the network calls the human-machine era, because of the pervasive nature of new technologies and their disruptive potential. Language is an essential aspect of this technology, but experts across the spectrum from linguistics to computer science tend to work isolated from each other. The LITHME initiative aims bridge that gap and bring experts from the different linguistic and computer science realms together to tackle potential issues and amplify the potential benefits of state-of-the-art language technologies. The network does this through eight Working Groups, i.e. WG 1: Computational Linguistics; WG 2: Language and Law; WG 3: Language Rights; WG 4: Language Diversity, Vitality and Endangerment; WG 5: Language Learning and Teaching; WG 6: Language Ideologies, Beliefs and Attitudes; WG 7: Language Work, Language Professionals; WG 8: Language Variation. Members of Concept Analytics Lab collaborate with WGs 1 and 3.

LITHME conference

The LITHME Conference brings together researchers and experts from various areas of linguistics and language technology to prepare and to shape language and technology research in the human-machine era. Justyna Robinson represented the research of Concept Analytics Lab at the LITHME conference by presenting a paper entitled ‘Machine-led concept extraction’. The talk instigated further discussions about the relationship between concepts, language, and NLP methodologies.  

LITHME training school

The LITHME training school seeks to bring researchers and professionals working on the interconnection between language and technology to come together and share ideas about multiple aspects of this new frontier. Sandra Young attended and shares some highlights below.

The training school is primarily a networking event. It was interactive and provided an excellent opportunity to meet people across a whole spread of research and industry fields. The international nature of the event also provided an array of participants to learn with and from. I found the eclectic nature of people’s backgrounds particularly inspiring: there were doctoral students to professors, sociolinguists looking at ethics and how technologies are changing research methods, to computer scientists working LLMs and using robots and teaching aids for autistic children. It was also enriching to be in a space with people from all over Europe (and beyond), to be able to share different experiences and the differentiated experience of the same technologies or elements through different linguistic lenses.

 

The training school fed us with a lot of information about different aspects of language technology and our world today. Of this, information relating to the unequal access to technology and availability of linguistic data has really embedded itself into my mind: forty per cent of the world’s population have no access to/do not use the internet. That is not far from half. When we talk about ‘today’s data-driven world’ we are excluding nearly half the world population. Then, who writes the internet, and in what language? English represents over 80% of the internet. And the content is written primarily by only certain people within these societies. The question of who language technology serves and who it excludes is a huge issue that is rarely the focus of conversation, and one that needs to be central when we are thinking that LLMs and the modelling of technologies will shape our society, our thoughts and what people take to be ‘true’.

 

But on a theoretical level, the question that interests me most was mentioned right at the beginning by Rui Sousa de Silva and Antonio Pareja Lora was the question of understanding. I have always been of the mindset that computers don’t understand what they are generating, not in the way we understand things. It is why we need the human element within technologies to provide this real-world view, why computers produce inconsistencies that strike us as strange. They work in a different and complementary way to us. But what about humans? I have thought about humans and understanding throughout my life as a translator and interpreter, often marvelling that we understand each other at all. But I had not given it much thought specifically in the context of language technology. Does it matter that computers don’t understand? How can the abilities of computers (lots of data, computing power) be leveraged to support humans where they excel (specialist expertise and a real understanding of texts and the world)?

The training school was a melting pot of minds: from tech to human, those embarking on their careers and those reaching the pinnacles of theirs, different languages, experiences and life journeys. The meeting of minds provided by LITHME is also a key element of our work at Concept Analytics Lab—the attempt to build bridges and work together to forward the language/technology divide through shared experience. In our little corner of work, our aims in that sense align very well with LITHME aims and we look forward to exploring further shared ideas and synergies.

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

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What can a conceptual analysis tell us about public attitudes to post-Brexit trade?

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What can a conceptual analysis tell us about public attitudes to post-Brexit trade?

by Rhys Sandow

Concept Analytics Lab were commissioned by the Prevention Research Partnership (PETRA) to investigate the attitudes towards trade expressed in responses to the Mass Observation Project’s 2021 UK Trade Policy directive. PETRA is a network of cross-disciplinary academics and other experts from NGOs and charities who are united by their goal of determining how trade agreements can be used to prevent disease and improve health. The long-form narratives from the general public gathered by the Mass Observation’s Trade Policy directive on the topic of trade deals that are unparalleled in scope.

Here at Concepts Analytics Lab, we employed both established and bespoke computational linguistic tools to extract key themes (concepts) in the data and then conducted corpus analysis to provide a close reading of these salient topics. Our analysis, which comprises 125 responses to the directive, totalling 56,840 words, identified the top 100 concepts that are characteristic of the Trade directive (its conceptual fingerprint, see Figure 1).

 

Figure 1: The top 100 concepts in the Mass Observation’s Trade directive.

Using these key concepts as our starting point, we conducted corpus analysis, from which we identified a range of themes in relation to trade policy including:

  • Ethical concerns
    • Human rights issues in China
    • Environmental impact of long-distance trade
    • Animal welfare in the USA and Australia
    • Likelihood of standard to decrease post-Brexit
  • A desire for health and environment to be priorities in any future trade deal
  • A perception that EU standards are world-leading
  • Leaving the EU is an opportunity to support local produce to a greater extent
  • A belief that trade deals will not impact individuals or their local communities
  • A belief that while environmental concerns were a priority for respondents, the government’s key concerns were financial

  • A general acknowledgement of a lack of awareness of the intricacies of trade agreements

The findings bear impact on our understanding of i) the public’s attitude towards trade agreements and how these vary between countries, ii) the disconnect between what the public want from a trade deal and the perceived agenda of the UK government, and iii) the value of clear communication between policy makers and the general public about trade deals and their implications. On a more methodological level, we showcase the value of employing a dual approach of conceptual and corpus analysis to provide an overview of key themes within a data set as well as a more detailed and contextualised investigation of stances and attitudes expressed in relation to these topics. But, most importantly, this research impacts the PETRA network in their research and shaping trade-related public policy in the UK.

For a more detailed account of our findings, you can read our full report here.

About Us

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

 

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Bridging the gap between computational linguistics and concept analysis

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Better together

by Eddie O’Hara Brown

Bridging the gap between computational linguistics and concept analysis

"Bridging The Gap" by MSVG is licensed under CC BY 2.0.

One of our priorities at the Concept Analytics Lab is to utilise computational approaches in innovative explorations of linguistics. In this post I explore the disciplinary origins of computer science and linguistics and present areas in which computational methodologies can make meaningful contributions to linguistic studies.

 

The documented origins of computer science and linguistics place the fields in different spheres. Computer science developed out of mathematics and mechanics. Many of the forefathers of the field, the likes of Charles Babbage and Ada Lovelace, were first and foremost mathematicians. Major players in the development of the field in the twentieth century were often mathematicians and engineers, such as John von Neumann and Claude Shannon. On the other hand, linguistics developed out of philology and traditionally took a comparative and historical outlook. It was not until the early 20th century and the work of philosophers such as Ferdinand de Saussure, when major explorations into synchronic linguistics began.

 

The distinct origins of computer science and linguistics are still visible in academia today. For example, in the UK and other western universities, computer science is situated in STEM subjects, and linguistics often finds a home with humanities and social sciences. The different academic homes given to linguistics and computer science often poses a structural barrier to interdisciplinary study and creation of synergies between the two disciplines. 

 

Recent research shows that the merging of linguistic knowledge with computer science has clear applications for the field of computer science. For example, the language model BERT (Devlin et al., 2018) has been used by Google Search to process almost every English-based query since late 2020. But we are only just beginning to take advantage of computational techniques in linguistic research. Natural language processing harnesses the power of computers and neural networks to swiftly process and analyse large amounts of texts. This analysis complements traditional linguistic approaches that involve close reading of texts, such as narrative analysis of language, discourse analysis, and lexical semantic analysis.

 

One particularly impressive application of computational linguistics in the analysis of semantic relations is the word2vec model (Mikolov et al., 2013). word2vec converts words into numerical vectors and positions them across vector space. This process involves grouping semantically and syntactically similar words and distancing semantically and syntactically different. Through this process corpora consisting of millions of words can be analysed to identify semantic relations within hours. However, this information, as rich as it is, still needs to be meaningfully interpreted. This is where the expertise of a linguist comes in. For instance, word2vec may identify pairs of vectors between which the distance increased across different time periods. As linguists, we can infer that the words these vectors represent must have changed semantically or syntactically over time. We can rely on knowledge from historians and historical linguists to offer explanations as to why that change has occurred. We may notice further that similar changes occurred amongst only one part of speech, or note that the change first occurred in language of a particular author or a group of writers. In this way, the two fields of computer science and linguistics necessarily rely on each other for efficient, robust, and insightful research.

 

At the Concept Analytics Lab, we promote the use of computational and NLP methods in linguistic research, exploring benefits brought by the convergence of scientific and philological approaches to linguistics. 

 

References

Devlin, Jacob, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova (2018) ‘Bert: Pre-training of deep bidirectional transformers for language understanding.’ Available at https://arxiv.org/abs/1810.04805

 

Mikolov, Tomas, Kai Chen, Greg Corrado, and Jeffrey Dean. (2013) ‘Efficient estimation of word representations in vector space.’ Available at https://arxiv.org/abs/1301.3781

 

About Us

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

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Covid-19 Crisis to Net Zero: A story of dedication and doubt in recycling

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Covid crisis to net zero: a story of dedication and doubt in recycling

by Sandra Young

In March 2022, the Concept Analytics Lab was awarded a grant from the Higher Education Innovation Fund (HEIF), run in partnership with the Sussex Sustainability Research Programme (SSRP). The call this year was aimed at addressing the critical challenges of Covid-19 recovery and climate change in an integrated way. We partnered with Africa New Energies (ANE), with their visualisation expertise. The Mass Observation project (MO) provided us with the data for an opportunity to apply our linguistic and computational analysis techniques to a new dataset.

Mass Observation directives focus on specific themes and ask volunteers called observers to write narrative responses to a series of questions on those themes. Every response is stamped with detailed information of each contributor-observer. In this case we studied the 2021 Household Recycling directive. This blog highlights key findings of our report and how our findings could feed into improving recycling performance in the UK.

 

What is waste?

We applied semantic corpus analysis to the 2021 MO Household Recycling directive to identify to identify key themes within the directive and then use this as a spring board to understand what people said about those themes and their positions on them. Waste, unsurprisingly, was one of those themes. We identified a number of near synonyms for waste, such as litter, debris and rubbish. We delved deeper by searching on the verbs that appear alongside the various words identified for waste, to identify what other objects are categorised as waste. Here we identified that a mix of different objects that are variably reused, recycled and thrown away depending on context:  
Figure 1: Collocates of reuse versus recycle.

Figure 1 shows us that many objects, depending on context, can either be reused or recycled: packaging, containers, waste (usually collocated as food, garden, household), pot, paper, plastic, bag.

 

Figure 2: Collocates of throw versus reuse.
Figure 3: Collocates of throw versus recycle.

In Figure 2 we see the perceived use of containers of different types in the way that they solely collocate with reuse and not throw (tubs and pots being types of containers). Jar is used in the context of both recycle and throw. When we look at the collocates this seems to be because of the contradiction between keeping, then throwing out if no use is found for said jars.

Here are some examples of the use of jars in context:

  • I do keep some lidded jars for when I make jams and chutneys and sometimes I keep plastic containers to use for sowing seeds in or if they have lids for storage.
  • Yes, I keep glass jars to reuse for leftovers, gardening, spices, herbs, food prep etc. I keep plastic containers from vegetables to use as dividers in the fridge. I reuse food bags and bread bags for leftovers and portioning items put into the freezer.
  • I regularly hang out a bag of used jam jars for a friend who returns the favour by dropping off delicious home-made preserves, pickles and jams.
  • I have a fondness for jars and biscuit tins, so some may linger in the garage until I find a use for them, or until I throw them out too.

Why is it waste?

Figures 1, 2 and 3 show us that packaging and plastic are important collocates for all three verbs (reuse, recycle and throw). When we look closer at the data we see this seems to be in relation to a number of issues: uncertainty, variation in services and multiplicity of packaging.

Here are some examples of the use of jars in context:

  • Items not recycled tend to be plastic film of food packaging, hard plastic and black pastic [sic] which is marked as unrecyclable.
  • We do not recycle black plastic, plastic bags, and polystyrene due to /a lack of facilities.
  • Plastic is the most difficult to recycle. Why can’t it all be recycled? (Like most people, we have to throw away as much plastic as we recycle) My wife and daughter are fanatical about it.
  • We can recycle most things but plastics are the most difficult items to get right.
  • I try to recycle as much as possible but also aim to reduce my consumption of goods that are plastic wrapped or in plastic-coated packaging that can’t be recycled.
  • I’m aware that black plastic food boxes or yoghurt pots can’t be recycled but uncertain about some clear plastic packaging for instance meat and fruit boxes.
  • XXXX Council has an excellent Waste Wizard on their website describing exactly what to recycle and how to prepare it. XXXX Council’s webguide is less detailed, and in general they recycle a smaller range of plastics and don’t accept tetrapacks as XXXX does.
  • In our area we are not able to recycle a huge amount of items – only plastic with numbers 1,2 and 3, for instance, so a lot of plastic packaging regrettably cannot be recycled
  • We find it annoying and frustrating to find so much plastic that cannot be recycled – e.g. plastic bags and containers – crisp bags, coffee packs, inner packing of biscuit/confectionery etc.

Where does it go?

Coupled with uncertainty about plastics and other types of recycling, respondents expressed doubt as to what happens to recycling once it is taken away.

  • I can’t say that I know what happens to the recycling once it is collected hence my very general answer but I do think I should find out.
  • I honestly don’t know what happens to our recycling once it is collected.
  • Do not really know what happens to the waste and whether it is put to good use.
  • I don’t know what happens with garden waste in terms of collection.

This is coupled with a desire to know more about what happens:

  • Its till a mystery, I don’t think local councils are transparent to what happens to our discarded rubbish and food waster.
  • I do wish our council would come clean and do a huge item in the local paper (or on video) showing us what happens to all our stuff!
  • Which types and numbers are acceptable is not given by the council, only vague guidance like plastic milk bottles are OK but not yoghurt pots – why?
  • A lot is dependant upon Government funding but there is much more than the council can do in educating the public perhaps by starting with schools.

Our duty

Despite this doubt and cynicism in the process, respondents showed their clear commitment to recycling as a process, accompanied with a feeling of duty.

  • I recycle because it is the right thing to do for environmental reasons.
  • I recycle because I believe it is my duty as a citizen to do so, it is part of my very small contribution to addressing climate change along with a general desire to, where possible, reduce my carbon footprint.
  • I recycle because I believe it is a responsible action to reduce waste to help the environment, wildlife and also less developed countries who are in immediate danger from the effects of climate change.

How can we improve?

The combination of lack of standardisation and information on the part of institutions such as the council, combined with this feeling of duty and responsibility as citizens on the part of the Mass Observation respondents, indicates that there might be a window of opportunity to intervene and improve recycling rates and quality through education and information sharing.

The findings in this report support research in other areas (Burgess et al (2021) and Zaharudin et al (2022) about the need for greater standardisation and reorganisation of recycling networks to maximise adherence to and performance of the recycling system. Our findings also suggest that another way to improve this would be the increase the information given to citizens about recycling processes, particularly in relation to what happens to recycling once it is collected.

 

References

Burgess, Martin, Helen Holmes, Maria Sharmina and Michael P. Shaver. (2021). The future of UK plastics recycling: One Bin to Rule Them All, Resources, Conservation and Recycling, January 2021, Vol. 164.

Zaharudin, Zati Aqmar, Andrew Brint, Andrea Genovese. (2022). Multi-period model for reorganising urban household waste recycling networks, Socio-economic planning sciences, July 2022.

 

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

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