Bibliographic record
Abstract
Using longitudinal data of 18- to 20-year-old youths from the Youth in Transition Survey (YITS), the present analysis identified and profiled Canadian postsecondary education dropouts based on the theoretical framework of Tinto (1993). Pertaining to characteristics of pre-postsecondary education conditions, dropouts tended to be male, set low postsecondary education goals, and have a history of dropping out and drug abuse in high school. Pertaining to characteristics of postsecondary education integration, dropouts demonstrated a first-year postsecondary education GPA of 60% or lower, an avoidance of volunteering on campus, and a lack of personal connections on campus. In addition, dropouts have previously contemplated quitting, have low sense of belonging, rely on social assistance, have neither institutional scholarships nor parental loans, are married, and are pursuing postsecondary programs in trade schools or technical schools. Integration into postsecondary education is far more critical to student attrition than pre-postsecondary education conditions. Puisant dans les données longitudinales d’une enquête de Statistique Canada auprès des jeunes en transition (Youth in Transition Survey), notamment la cohorte des 18 à 20 ans, la présente analyse a identifié et souligné, selon le cadre théorique de Tinto (1993), les individus ayant décroché en cours d’études postsecondaires. Ceux qui décrochent avant les études postsecondaires sont souvent masculins, ils se fixent des objectifs limités relatifs aux études supérieures et ont des antécédents impliquant des abandons scolaires et la toxicomanie au secondaire. Parmi les caractéristiques des décrocheurs au niveau postsecondaire, notons une moyenne globale inférieure ou équivalente à 60% lors de leur première année d’études supérieures, une absence de participation aux activités bénévoles sur le campus et un manque de liens personnels sur le campus. De plus, les décrocheurs ont souvent déjà pensé à abandonner, manifestent un faible sentiment d’appartenance, comptent sur l’assistance sociale, n’ont pas reçu de bourses institutionnelles ni de prêts de la part de leurs parents, sont mariés et poursuivent des études postsecondaires dans des écoles techniques ou des écoles de métiers. L’intégration joue un rôle beaucoup plus critique dans le taux d’abandon des étudiants au niveau postsecondaire qu’au secondaire.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".