Les effets des programmes d’été de littératie: Les théories sur les opportunités d’apprentissage et les élèves « non traditionnels » dans les écoles de langue française en Ontario
Bibliographic record
Abstract
According to studies from the United States and English Canada, student achievement gaps grow over the summer months when children are not attending school, but summer literacy interventions can reduce those gaps. This paper presents data from a quasi-experiment conducted in eight Ontario French language school boards in 2010, 2011 and 2012 for 682 children in grades 1-3. Growth in literacy test scores between June and September are compared for 361 attendees of summer literacy programs and 321 control students. Summer program recruits initially had lower prior literacy scores and grades, and tended to hail from relatively disadvantaged social backgrounds. Yet, summer programs narrowed those pre-existing gaps. Effect sizes from a variety of regression and propensity score matching models ranged from .32 to .58, which is quite sizeable by the standards of elementary school interventions and summer programs. Effects were stronger among students whose parents reported not speaking French exclusively at home. Our paper considers learning opportunity theory in light of the “non-traditional” student in Ontario French language schools.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".