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Record W3123993094 · doi:10.1177/1521025120987993

A Long-Term Study of What Best Predicts Graduating From University Versus Leaving Prior to Graduation

2021· article· en· W3123993094 on OpenAlexafffundabout
Teena Willoughby, Victoria W. Dykstra, Taylor Heffer, Joelle Braccio, Hamnah Shahid

Bibliographic record

VenueJournal of College Student Retention Research Theory & Practice · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGraduation (instrument)PsychologyMental healthMedical educationGerontologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Despite the importance of obtaining a university degree, retention rates remain a concern for many universities. This longitudinal study provides a multi-domain examination of first-year student characteristics and behaviors that best predict which students graduate. Graduation status was assessed seven years after students entered university. Participants (N = 1017; 71% female; mean age in Year 1 was 19 years) enrolled in a Canadian mid-sized university completed a survey, provided their enrollment status over the next 6 years (regardless of whether they left university), and consented to have their grades and status provided by the Registrar. Overall, 79% of students graduated by Year 7 (44% in 4 years). The strongest predictor of graduation was first-year grades. Social engagement in the university also predicted graduation. Surprisingly, mental health was not a significant predictor of graduation. Only a minority of students may experience mental health difficulties to such an extent that it affects their ability to succeed at university.

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)0.018
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.001
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 head0.119
GPT teacher head0.489
Teacher spread0.370 · 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.

Study designQualitative
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

Citations6
Published2021
Admission routes3
Has abstractyes

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