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Record W3034013214 · doi:10.1177/0731121420921903

Choosing and Changing Course: Postsecondary Students and the Process of Selecting a Major Field of Study

2020· article· en· W3034013214 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.

Bibliographic record

VenueSociological Perspectives · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsWestern University
FundersDivision of Undergraduate EducationNational Science Foundation
KeywordsExtant taxonRelevance (law)PsychologyHigher educationPostsecondary educationProcess (computing)Field (mathematics)Mathematics educationVariation (astronomy)Demographic economicsPolitical scienceEconomicsEconomic growthComputer science

Abstract

fetched live from OpenAlex

Much prior research has examined the individual-level, major-specific, and institutional correlates of college students’ choice of major, as well as the variation in labor market outcomes associated with this important choice. Extant accounts, however, largely overlook the process by which individuals change their major throughout college. This study provides a comprehensive description of major switching, and considers its relevance to concerns about stratification in postsecondary education. Drawing on survey and transcript data from students at three large universities in the United States, I find that switching is widespread, and that many students change their majors multiple times. Students appear to change majors in an effort to better fit their interests and abilities, as students seek out majors that are generally less competitive and easier. Major change further contributes to gender segregation, particularly as women leave science, technology, engineering, and math (STEM) fields after initially selecting these at lower rates than men.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.039
GPT teacher head0.463
Teacher spread0.424 · 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