Following the Money? The Impact of Educational Spending on Student Achievement in Saskatchewan, Canada
Bibliographic record
Abstract
The link between public school funding and student outcomes in the United States has been debated for years. In order to study the causal effects of per-student spending on academic achievement, researchers often study natural experiments caused by changes to school finance policies, which create shocks to individual districts’ funding levels. However, Canadian reforms have rarely been studied using these quasi-experimental methods. I supplement this literature, analyzing the effects of per-student expenditures on high school graduation rates and course completion in the Canadian province of Saskatchewan. Saskatchewan reformed its school finance laws between 2009 and 2012; I employ a difference-in-differences exposure model to evaluate the effects of these changes on students’ educational attainment. I find that a $1,000 increase in annual per-pupil expenditures leads to a 0.257 percentage-point increase in the share of students graduating high school within 3 years of beginning Grade 10. However, I find null effects on the share of students graduating high school within 5 years of beginning Grade 10, as well as the proportion of students attaining 8 course credits per year.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".