Federal Overreach: The Attestation Controversy and the Canada Summer Jobs Program, 2017-2019
Bibliographic record
Abstract
Our paper investigates the impacts of the 2018 attestation requirement of the Canada Student Jobs program (CSJ) compared to that of the no-attestation version of 2017, and that of the revised CSJ attestation box of 2019. We found:(1) Christian groups (mostly Catholic and various evangelical Christian denominations) collectively received less than half the funds they received in 2017, and lost just over 3,000 jobs in 2018, or just under half the jobs secured 2017. In 2019 religious-based groups regained about 2,700 jobs.(2) what jobs the religious groups lost in 2018 were picked up by non-religious applicants. The latter received a modest increase in funding in 2018 over the previous year, and another increase in 2019.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".