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Record W4407070145 · doi:10.1016/j.ssaho.2025.101289

Who transitions into post-secondary education and why? A systematic review of the Canadian landscape

2025· review· en· W4407070145 on OpenAlexafffundabout
Alexandra Pulchny, Karen Robson, Robert S. Brown

Bibliographic record

VenueSocial Sciences & Humanities Open · 2025
Typereview
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsYork UniversityMcMaster University
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsSystematic reviewGeographyEnvironmental planningPolitical scienceMEDLINE

Abstract

fetched live from OpenAlex

Decades of research have documented rates of student transitions into post-secondary education (PSE). A large majority of secondary students expect to obtain some level of PSE and are either motivated by their own personal interest, parental influences, or economic reasons. In 2020, The Organization for Economic Co-operation and Development (OECD) reported that Canada had an 86% secondary graduation rate. The percentage of those students who transitioned directly into post-secondary institutions is unclear, as enrolment rates can include direct and delayed entry. Using systematic review methods and reflective thematic analysis, we identified trends in the literature that cite family influences geographic influences, sex, various school influences, and race and ethnicity as key impacts on students’ decisions to transition to PSE.

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)0.010
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.908

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0200.032
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.082
GPT teacher head0.430
Teacher spread0.348 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes3
Has abstractyes

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