Impoverished Neighbourhoods & After-School Programs
Bibliographic record
Abstract
This paper examines the quality of Ontario’s after-school program as implemented by Rapport by using Tuason et al.’s (2009) criteria. The goal of this study is to answer the following questions: How the three core areas of the program are implemented and what activities are offered in the three core areas? How staff members and participant perceive the program and how the program impacts the lives of the participants? After-school programs have become an essential part of impoverished communities over the past three decades. The need of quality after-school programs in disadvantaged neighbourhoods has never been higher. Children residing in disadvantaged neighbourhoods are vulnerable to countless harms such as: crime, victimization, drugs, dysfunctional family systems, abuse and etc. Children are most vulnerable during the after-school hours and require adequate supervision. Through qualitative research methods, data was gathered through focus group interviews with participants attending Ontario’s after school program at Dunrankin public school in Malton Ontario. Additionally, data was also gathered through one on one interviews with staff members and program coordinator of the program. This study revealed Rapport offered the participants a quality after-school program.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 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".