Collective post‐traumatic growth: Validating and measuring positive change in the collective self among victims of sexual violence
Bibliographic record
Abstract
Abstract Across the world, women's personal responses to gender‐based violence are increasingly political. In the current paper, we consider whether positive changes in the collective self, arising from personal experience of gender‐based violence, which may lie at the heart of this phenomenon, can be evidenced. Four studies are reported that evidence and validate a proposed construct that reveals collective post‐traumatic growth (PTG) among people who have experienced sexual violence. Confirmatory factor analyses, including a preregistered analysis, indicate that collective PTG is a multidimensional construct and is distinct, yet related to personal PTG. A longitudinal analysis offers evidence of stability and highlights the importance of collective efficacy and group solidarity in determining collective PTG over time. A final experimental study provides evidence of collective PTG determining people's emotional responses to reminders of their trauma. Taken together, these studies emphasize the significance of collective growth as an often overlooked, though positive and important, sociopolitical response to direct experiences of very personal trauma.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".