Collective Agency in Reparation Politics: A Contentious Politics Perspective on Victim Mobilisation in Northern Ireland
Bibliographic record
Abstract
This article contributes to a better understanding of the collective agency of survivor organisations in Transitional Justice (TJ) processes by studying their claims for reparations as contentious politics. Examining two different survivor groups in Northern Ireland, we argue that applying concepts from social movement theory to understand victim groups in TJ is valuable in four ways: Firstly, it facilitates an analytical assessment of how and why survivors organise, and allows to systematically unravel the factors impacting mobilisation. Secondly, approaching survivor groups as strategic political actors engaged in contentious politics shifts the focus back to their agency as drivers of TJ. Thirdly, it helps to understand survivor groups “from within” and reveals the diversity and complexity of survivors’ identities, strategies and demands in transitional settings. Lastly, focusing on survivors’ collective agency helps to move beyond a liberal human-rights based approach to victim organisations and to consider groups acting within different moral frameworks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.036 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".