Bibliographic record
Abstract
A study conducted by Dr. Alan King in the early 2000s exposed low secondary school graduation rates and a variety of indicators of a student's likelihood of success in graduating. Premier Dalton McGuinty's Liberal government responded with a reform aimed at changing educational practices through the Student Success/Learning to 18 Strategy (SS/L18) in 2003 and Policy/Program Memorandum No. 137 in 2005. This drove a province-wide effort to support students ‘in-risk' of not graduating with a multitude of new resources and policies. Ontario's secondary school graduation rates have since increased to 82 percent, however, a variety of barriers to student success remain both socially and culturally in Ontario schools. The absence of student social and cultural capital can diminish educational opportunities for students which is problematic for an equitable system. This chapter explores the history of Student Success initiatives, the unique role played by Student Success Teachers and L.E.A.D. teacher candidates, and further areas of need to be addressed in closing the gap in education.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.034 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".