Guest Editorial: Mass Atrocity and Collective Healing: New Possibilities for Regenerating Communities
Bibliographic record
Abstract
This Special Issue brings together five articles from different disciplines. It aims to contribute to the emergent critical voices in research about collective trauma and collective healing by introducing novel perspectives and inviting further debates on the relevant issues evoked. For this reason, the Special Issue focuses on collective healing through a number of prisms. First, it delves into the notions of wounding and trauma, with a view to advance a well-argued theoretical framework for understanding collective healing. Second, it identifies underlying ethical pillars for collective healing, especially the principles of equality and well-being that affirm human dignity founded on our intrinsic non-instrumental value as persons. Third, it interrogates one of the deeply seated root causes of transatlantic slavery, and establishes a connection between capitalist expansion and systematic subjugation of human beings to brutal forces for the sake of materialistic production and wealth accumulation. Thus, this Special Issue attempts to survey historical dehumanisation in some of the mass atrocities, probe their continued legacies in contemporary societies in Africa, Europe, and the Americas, and highlight some of the political, psycho-social and grassroots approaches to collect healing in various contexts. In doing so, it further reflects on the conceptual, methodological and structural challenges involved when moving towards collective healing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".