L'echec scolaire en Amérique du Nord: un phénomène insidieux pour und grand nombre d'enfants et d'adolescents: un phénomène insidieux pour und grand nombre d'enfants et d'adolescents
Bibliographic record
Abstract
L'echec scolaire en Amerique du Nord constitue une problematique tres importante et fort preoccupante pour l'ensemble des acteurs scolaires. L'ampleur et la gravite de ce phenomene se laissent d'ailleurs difficilement circonscrire parce qu'il n'existe pas de consensus quant a la definition de la reussite et de l'echec a l'ecole. Le present article rend compte de l'echec scolaire, plus particulierement aux Etats-Unis et au Canada, en recoupant plusieurs donnees statistiques provenant d'etudes concernant les eleves en difficulte d'apprentissage, les eleves en situation de retard scolaire et les eleves decrocheurs. Ces donnees fournissent un apercu de l'etendue de l'echec scolaire dans les ecoles primaires et secondaires dans ces pays. Elles font notamment ressortir que ce phenomene touche un nombre beaucoup plus important de garcons que de filles et que ses origines et ses manifestations sont multiples.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".