Posttraumatic Growth Following WWII: Polish people who were child refugees in New Zealand tell their story
Bibliographic record
Abstract
Posttraumatic growth (PTG) denotes positive changes that arise due to one’s struggle with traumatic experiences. Despite growing interest in this field since the 1980s, PTG among individuals who have experienced trauma in childhood has been relatively understudied, and the process by which it occurs requires further examination. The narratives of 51 elderly Polish people who narrated their WWII experiences, deportation to Soviet labour camps, and migration to New Zealand as refugee children were analyzed by thematic content analysis. PTG was identified using the 5 factors of the Posttraumatic Growth Inventory: Relating to Others, New Possibilities, Personal Strength, Spiritual Change, and Appreciation of Life. The most commonly mentioned PTG dimension overall and among women was Changes in Interpersonal Relationships, a dimension that reflects a change that includes feeling closer to others, improvements in getting along with others, and a better understanding of others. Men reported instances of Changes in Perception of Self more frequently than women, though further analysis would be required to confirm significant gender differences. These results reveal that the experience of childhood trauma and migration may be affected by a country’s welcome practices towards refugees, and that these experiences can influence personal transformations that occur across the lifespan.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".