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| Format: | Recurso digital |
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Zenodo
2026
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| Matèries: | |
| Accés en línia: | https://doi.org/10.5281/zenodo.20263163 |
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- <p>Tables from a corpus-level risk-classification analysis of the publications of an EU-funded research programme on artificial intelligence in the political-communication domain. The classification scheme — four axes (topic, venue, geography, disciplinarity), per-axis operationalisation, and risk-gradient thresholds — is documented in the companion framework documentation (see relatedIdentifiers).</p><p>In order to ensure the analysis stays at institutional level (avoiding personal attribution to researchers), the tables refer to individual publications by an opaque identifier (<code>pub_uid</code>, P001–P0NN) and contain no bibliographic information (titles, author names, venue names, DOIs). Aggregations report counts and percentages across the 75-publication corpus.</p><p>Contents (in <code>derived-tables/</code>): a per-publication enriched table (year, venue type, data source, classification levels, risk score) plus 27 aggregation tables along axes and cross-tabulations (per-axis distributions; risk by venue, by year, by discipline; channel-mismatch; ethics-authorisation and DPIA counts; year-trend; country and topic risk; LLM use; data-source and output-category breakdowns).</p><p>A subsequent version (2.0.0) will add the R analysis scripts, the rendered summary tables, the figures, and the summary statistics that consume these tables to reproduce the empirical reporting of the corresponding manuscript.</p>