Theorizing Age and Generation in Migration Contexts: Towards Social Age Mainstreaming?
Bibliographic record
Abstract
This paper proposes social age as an analytical framework within which to understand and respond to age and generation in migration contexts. It argues that comprehensive social age analysis can lead to greater age sensitivity in migration research, policy and programming. As such, this introduction situates the empirical studies in the special issue and draws on them to test, challenge and inform the social age analytical framework. Le cadre analytique que nous proposons dans cet article pour comprendre et trouver des réponses à la question des âges divers et des générations dans des contextes de migration est l’âge social. Nous soutenons qu’une analyse compréhensive de ce dernier peut mener à une plus grande sensitivité envers la question de l’âge dans la recherche, la politique et la programmation sur la migration. En tant que telle, cette introduction donne dans ce numéro spécial une place aux études empiriques, dans lesquelles elle s’appuie pour tester, mettre au défi et alimenter le cadre analytique de l’âge social.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".