Metadata of interviews with Elected and appointed policy actors; Government officials and civil servants; Experts, Activists, Lobbyists and Citizens

Research Objectives The interviews were designed to reconstruct practical and experiential knowledge about grievance politics and emotional dynamics across institutional, expert, activist, and citizen perspectives. They also aimed to provide an empirically grounded basis for interpretive, narrative, and practice-oriented analyses in WP4, WP5, and WP6. Three overarching research questions guided the data collection: how different actors understand, experience, and manage emotions related to grievance politics; how emotional mechanisms such as resentment, indignation, and moral outrage are embedded in professional practices and citizen engagement; and how actors reflect on possibilities for mitigating grievance dynamics. Summary of Methodology The primary data collection method is semi-structured, in-depth interviews lasting 45 to 60 minutes, conducted with four target populations: EAA (Elected and appointed policy actors), GOCS (Government officials and civil servants), FPE (Foreign policy experts, experts, activists and lobbyist) and C (Citizens) expressing grievances. Sampling Strategy A non-probability, purposive sampling strategy was used, supplemented by snowball sampling and survey-based recruitment. The consortium conducted online or in person approximately 140 interviews across multiple countries and languages. Description of methods Interview guides were developed collaboratively across partner teams through an iterative process of co-design, testing, and revision, producing a seven-block questionnaire. Data sources The dataset is based on the interviews conducted by the various teams, covering the four target populations groups identified (EAA, GOCS, FPE and C). Fieldwork dates December 2025-June 2026 Data collection procedures The process followed a structured sequence across all partner teams. First, potential interviewees were identified through purposive sampling based on their relevance to specific interview sets, their professional expertise, and their political significance. Second, interview teams discussed and agreed on data collection categories for the shared registry, covering interviewee codes, positions held, and contact details. Third, snowball sampling was used to expand the pool, drawing on interviewees' political networks, previous positions, and social media presence. Fourth, an internal interview registry was populated and maintained for GDPR and data protection purposes. Fifth, potential participants were contacted using predefined templates that explained PLEDGE’s objectives, the specific thematic and set-related aims of the interview, and the interviewee's data protection rights. Sixth, interview dates and modes (online or in person) were agreed according to interviewees' availability, and interviewers were designated. Seventh, at the start of each interview, PLEDGE’s objectives and the interview's specific aims were restated, and permission for audio or video recording was requested. Eighth, audiovisual data was stored locally on university devices and on secure institutional servers, according to each PLEDGE partner’s ethics guidelines. Dataset Content The dataset contains the following information: Interview ID Set Country Gender: W (woman); M (man); N (non-binary/other) Age: 1= less 35; 2=36 to 54; 3= more than 55) Date of Interview Interviewer 1 Interviewer 2 Duration: Hours: Minutes: seconds Recording quality: Good; Moderate; Difficult Transcription software used Translation software used Date final document with transcript and translation generated Ethics Approval Ethical approval was granted by the Research Ethics committees at the ELTE Centre for Social Sciences, King’s College London, LUND University, National and Kapodistrian University of Athens, University of Valencia, University of Southampton and Vrije Universiteit Brussel. GDPR Compliance The metadata document does not contain direct personal identifiers. Data Anonymisation The document does not contain any personal data that would enable the interviewees to be identified. Conditions for Reuse Reuse should follow the licence specified in the Zenodo record. Users should properly cite the dataset and comply with GDPR requirements, platform-specific restrictions, and PLEDGE data management guidelines.