Profiles of Posttraumatic Growth Following an Unjust Loss
Bibliographic record
Abstract
The dominant model of posttraumatic growth (PTG) suggests that growth is precipitated by significant challenges to one's identity or to core assumptions that give one's life meaning, and develops as one goes through meaning-making or schema reconstruction processes. Other perspectives suggest, however, that such growth occurs by other means. We use a numerically aided phenomenological approach to elucidate common profiles of growth in a sample of 52 adults who lost a loved one in a traumatic mine explosion 8 years earlier. Of the three clusters extracted, 1 captured the essence of the PTG model, including threat to sense of self, meaning-making, and personal growth; 1 featured an inability to find meaning and an absence of growth; and 1 featured minimal meaning threat with modest growth. Those most likely to report PTG interpreted the experience as threat to self, with growth coming from development of new self-understanding. The data suggest that a better understanding of the processes of PTG may be realized by taking a more refined approach to the assessment of loss and growth, and by drawing distinctions between personal growth and benefits.
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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 | 0.001 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".