MétaCan
Menu
Back to cohort
Record W3024024579 · doi:10.1257/pandp.20201052

A Pareto-Improving Way to Teach Principles of Economics: Evidence from the University of Toronto

2020· article· en· W3024024579 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAEA Papers and Proceedings · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInnovations in Educational Methods
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsDemographicsMathematics educationDisciplinePareto principleEconomics educationLiteracyPsychologyMedical educationSociologyStatisticsPedagogyMathematicsSocial scienceMedicineDemographyPrimary education

Abstract

fetched live from OpenAlex

University of Toronto undergraduates can choose between conventional and literacy-targeted (LT) principles of economics courses. We compare demographics and performance in subsequent courses for 13,000 students over 11 years and find that LT courses attract a greater percentage of female and domestic students; conditional on meeting grade thresholds, LT students do just as well in intermediate theory and statistics courses as conventional principles students; women do as well or better than men in intermediate theory and statistics courses. With appropriately chosen thresholds, departments offering LT courses can preserve subsequent disciplinary rigor and address underrepresentation of women and minorities.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.063
GPT teacher head0.302
Teacher spread0.239 · 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