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Record W4386498249 · doi:10.1111/ruso.12510

Does Geography Matter? A Regional Analysis of Early Transfer within Ontario Post‐Secondary Education*

2023· article· en· W4386498249 on OpenAlexaffabout
Yujiro Sano, Cathlene Hillier, Roger Pizarro Milian, David Zarifa

Bibliographic record

VenueRural Sociology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsCanadian Association for the Study of Adult EducationUniversity of TorontoCrandall UniversityNipissing University
Fundersnot available
KeywordsGeographyDrop outDemographic economicsEconomic geographyDemographyRural areaEconomic growthSociologyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Abstract The relationship between geography and early transfer behavior has received limited empirical attention. In this study, we track six cohorts of university and community college entrants to examine differences in the early pathways they travel through Ontario post‐secondary education (PSE), paying particular attention to how transfer pathway uptake by students in the province's rural north might vary from those in the more urbanized southern regions. Overall, we observe only modest regional differences in early transfer pathway uptake, with parental income proving to be a more constituent predictor of transfer. However, we do find more sizable net regional differences in the propensity that students will drop out within two years of entering PSE, with northern students being significantly more at risk of leaving PSE in their early years.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.121
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.287
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2023
Admission routes2
Has abstractyes

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