“YouTube helps us a lot.” Media repertoires and social integration of Iraqi and Syrian refugee families in Germany
Bibliographic record
Abstract
Cet article examine les répertoires médiatiques de 10 familles de réfugiés syriens et 10 iraquiens (n=100) dans la ville d'Erlangen, en Allemagne. En nous fondant sur la théorie du répertoire médiatique (Hasebrink et Hepp 2017) et grâce à une approche qualitative combinant plusieurs méthodes de collecte de données (entretiens qualitatifs, groupes de discussion et dessins du répertoire médiatique), nous analysons comment les pratiques et dispositifs médiatiques cumulatifs des familles de réfugiés (répertoires médiatiques) sont reliés à leur intégration sociale et culturelle dans leur société d'accueil. Nos constatations indiquent que les répertoires des médias mettent en lumière diverses pratiques qui reflètent les efforts d'intégration des réfugiés dans leur société d'accueil. Les participants qui avaient surtout des réseaux et des répertoires centrés sur le domicile ont plus de mal à s'intégrer que ceux qui ont plus de contenu allemand et qui ont des réseaux basés dans la société d'accueil.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".