"Street Kids": Towards an Understanding of Their Motivational Context.
Bibliographic record
Abstract
La presente recherche visait a etudier les comportements et les buts quotidiens d'un echantillon de jeunes sans-abri en milieu urbain, ou comme ils preferent se faire appeler « des jeunes de la rue ». La difficulte de choisir un echantillon temoin approprie a ete surmontee en comparant des jeunes de la rue a deux echantillons distincts; des etudiants universitaires et des jeunes d'un club communautaire dans un quartier pauvre. Une entrevue standard a ete menee au cours de laquelle les jeunes devaient, un a un, se rappeler leurs comportements quotidiens, d'heure en heure, et ils etaient notes sur une echelle de dix points, sur une serie de questions portant sur la motivation, les modeles de comportement, la confiance et le bien-etre psychologique et physique. Les resultats revelent que les jeunes de la rue ne semblent pas avoir un ensemble coherent de buts a moyen et a long terme. De plus, ils n'ont pas confiance envers les autorites et ne les respectent pas, non plus qu'ils ne jouissent d'amities stables reposant sur la confiance et l'admiration. Cependant, le petit nombre de jeunes qui ont un ami de confiance sont davantage motives de facon intrinseque et ont tendance a se sentir moins irritables et moins anxieux.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".