Introduction
In 1948, the United Nations declared (1948, art. 21) democratic participation to be a fundamental right worldwide. However, data from the Economist Intelligence Unit’s Democracy Index 2023 show that only 24 countries, out of 167 scrutinised, can be considered as full democracies, where citizens can fully participate in deliberative and participatory processes. The rest are classified as flawed democracies, hybrid regimes, or authoritarian regimes, where democratic participation is limited.
Even in full democracies, millions of people with communication difficulties are excluded from taking part in democratic processes due to language barriers. Among others, people with intellectual disabilities, senior citizens and migrants may be unable to fully engage in participatory processes where topics are publicly discussed, if they struggle to read, write or comprehend the complex language used in such processes—not to mention deliberative processes where the decisions are made.
The iDEM project
The iDEM project, funded by the European Union and UK Research and Innovation (UKRI) and co-ordinated by Barcelona’s Pompeu Fabra University (see iDEM 2024), seeks to change this situation by creating inclusive, accessible, and unbiased democratic spaces for such marginalised communities. This goal is pursued by easy-to-read language, advanced artificial intelligence and natural language processing.
In particular, iDEM will test an app that is capable of simplifying written and spoken texts in democratic spaces. While the test is scheduled for 2026, iDEM has employed a mixed-methods approach to identify 14 main barriers to participation in democratic spaces. Among these, communication challenges are the most significant, as they affect how information is delivered, understood and discussed. These participation barriers manifest at various stages of democratic processes, such as during participants’ recruitment, or during or after the deliberation. In this context, key actors – like facilitators, policymakers, and support networks – can mitigate these barriers, with tools like assistive technologies, visual tools and digital platforms. However, the effectiveness of these tools depends highly on their adaptability to the needs of individuals with communication difficulties.
Based on the identification of complexities in written texts carried out by the University of Leeds, the app can turn standard written and spoken texts into easy-to-read language. This is a valuable resource specifically designed for people with intellectual disabilities that uses simple words, simple sentences, and simple concepts to deliver a message (see Inclusion Europe 2024). Because the app produces an intralingual translation of the source text, strategies have been identified to prompt the AI-based process to produce a text that is usable in democratic processes. These are based on the strategies identified by Eugeni and Gambier (2023) in the field of diamesic translation, that is speech-to-text reporting, and adapted to the specific needs of this form of translation, which can be identified as diastratic (Eugeni, 2020): from the language variation used by a social group into that of another group. In this case, it implies turning standard language into easy-to-read language.
Strategies in turning English into Easy-to-Read English
To do so, the first and most immediately identifiable strategy is transcript, which can be assimilated to the traditional direct translation used when two languages are involved in the translation (Vinay & Darbelnet, 1958). In transcripts, the words of the source text are left unchanged. Other traditional strategies include:
- Transposition (Vinay & Darbelnet, 1958), or a change in the word class, especially when a noun does not mean a physical object or a verb does not mean an action (e.g. my reasoning goes… > I think that…)
- Modulation (Vinay & Darbelnet, 1958), or the distribution of information in a linear order (e.g. Starmer became PM after serving as a lawyer > Starmer was a lawyer. Now Starmer is the Prime Minister)
- Omission (Chesterman, 1997) of features of orality (e.g. well, uh, I am hungry > I am hungry), rhetorical constructs (e.g. The fact is that I do > I do), abstract concepts, or other elements considered unnecessary or misleading (e.g. Sir Keir Starmer is for real an interestingly new face in the current political arena > Starmer is a new politician)
- Explanation (Chesterman, 1997) of words that are given for granted (e.g. the present agreement is signed by Carlo and Eero > When people want to decide something they sign a document. This document is called an agreement. Carlo and Eero signed this agreement), or considered as not clear like tropes, schemes, acronyms, deixis or even hidden grammar
- Illocutionary change (Chesterman, 1997), or making explicit what is implied (e.g. Couldn’t we say George’s sense for diplomacy could be improved? > George is not diplomatic).
A last strategy that is specific to the simplification of standard texts into easy-to-read language is synonymy, intended as the consistent use of a common and general word instead of a more complex, abstract or specific one. Synonyms can be
- pragmatic, like proper names being generalised (e.g. Starmer > the Prime Minister), abstract words being made more concrete (e.g. the leadership > the Prime Minister), or acronyms spelled out (e.g. the PM > the Prime Minister)
- semantic, like hypernyms (e.g. barrister > lawyer), hyponyms (e.g. faculty staff > teachers), or stereotypes (e.g. ponder > think; dramatically > very)
- grammatical, like negations being turned into positive clauses (e.g. I don’t hate you > I love you), passive voices into active (e.g. John was hit by a car > A car hit John), or pronouns into their referent even if redundant (e.g. I have bought a sandwich but it is full of ketchup and I don’t like it > I have bought a sandwich. The sandwich is full of ketchup. I don’t like the sandwich).
Once complexities are identified, these strategies will be used by the app to turn them into their easy-to-read versions, which can then be used to understand a document used in a participatory process or discussions of a topic in a deliberative one. These will hopefully make democratic participation quicker, smoother and allegedly more inclusive, to the benefit of all stakeholders.
Carlo Eugeni is Tiro’s Scientific Adviser.
REFERENCES
Chesterman, A. (1997) Memes of Translation. The spread of Ideas in Translation Theory. Amsterdam & Philadelphia: John Benjamins.
Economist Intelligence Unit (2023) Democracy Index. Available at https://www.eiu.com/n/campaigns/democracy-index-2023/
Eugeni, C. & Y. Gambier (2023), La traduction intralinguistique – les défis de la diamésie, Timisoara – Editura Politehnica Available at https://www.intersteno.org/book-order-la-traduction-intralinguistique-les-defis-de-la-diamesie/
Eugeni, C. (2020) “Human-Computer Interaction in Diamesic Translation. Multilingual Live Subtitling”. In Dejica, D., Eugeni, C. and A. Dejica-Cartis (eds.) Translation Studies and Information Technology – New Pathways for Researchers, Teachers and Professionals, Timișoara: Editura Politehnica, Translation Studies Series, pp. 19-31. Available at https://www.researchgate.net/publication/345803837_Human-Computer_Interaction_in_Diamesic_Translation_Multilingual_Live_Subtitling
iDEM (2024). Innovative and Inclusive Democratic Spaces for Deliberation and Participation. Available at https://idemproject.eu/
Inclusion Europe (2024). Information for all: European standards for making information easy to read and understand. Available at https://www.inclusion-europe.eu/easy-to-read-standards-guidelines/
United Nations (1948). Universal Declaration of Human Rights, available at https://www.un.org/en/about-us/universal-declaration-of-human-rights
Vinay, J. P. & Darbelnet, J. (1958) Stylistique Comparée du Français et de l’Anglais: Méthode de Traduction, Paris, Didier.
This document is part of a project that has received funding from the European Union´s Horizon Europe research and innovation program under the Grant Agreement No. 101132431 (iDEM Project). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. UOL was funded by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (grant number 10103529).
