Ukrainian Female War Refugees in Poland: Trauma and Emancipation
Bibliographic record
Abstract
This article is part of narrative research that explores how storytelling helps individuals understand the world and how they interpret the stories they share. The study, conducted by the authors between April and May 2022, involved sixteen women who were war refugees from Ukraine, aged between 29 and 52. The participants came from various regions of Ukraine, and all had children, with the oldest being 15 and the youngest 3. Most of the women were married, some had partners, and one was a widow. They left their homeland at different times, between March 3 and 23, 2022, and by the time of the study, they had been in Poland for a period ranging from four weeks to three months. Given the length of the article, the authors chose to focus on two specific contexts of the research: trauma and emancipation. The analysis and interpretation of the interviews include excerpts from the participants' statements. These statements are transcribed, treated as research data, and interpreted through narrative analysis to uncover meanings related to the socio-cultural context. The research method used positions the participants as creators of narratives, which allows them to express themselves as experts in their own experiences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".