Bibliographic record
Abstract
Des membres appartenant a des groupes de survivants de 1'Holocauste et des participants a des regroupements de survivants ont ete invites a remplir des batteries de questionnaires qui renfermaient deux mesuresde l'attribution. Une des mesures demandait aux participants de donner leur point de vue sur les facteurs qui leur ont permis de survivre pendant 1'Holocauste; l'autre mesure employee etait l'Attributional Style Questionnaire (ASQ), une mesure type des styles d'attribution. Les resultats ont ete compares aux reponses donnees par des repondants juifs du meme âge, qui ont reussi a se soustraire de la persecution nazie pendant la periode de 1'Holocauste. En ce qui a trait aux facteurs de survie pendant 1'Holocauste, les survivants ont mentionne un nombre de facteurs considerable; en outre, 91 % des survivants, mais seulement 51 % du groupe temoin, ont mentionne des facteurs externes (p. ex., la chance, l'aide provenant des autres) et le patron inverse (71% par opp. a 34%,), dans le cas des facteurs internes comme la force psychologique et la determination. Aucune difference intergroupe significative n'a ete observee dans l'Attributional Style Questionnaire en fonction du sexe et de l'âge du groupe (survivants par opp. au groupe de comparaison).
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".