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Record W6964556069 · doi:10.25740/vq250vq2123

Following the Money? The Impact of Educational Spending on Student Achievement in Saskatchewan, Canada

2022· article· en· W6964556069 on OpenAlexaboutno aff

Bibliographic record

VenueStanford Digital Repository · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)Student achievementAcademic achievementNatural experimentOrder (exchange)Public financeEducation economics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.309
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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