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Record W7139435810

Did non-standard undergraduate medical degrees widen access at eighteen British medical schools (2002 and 2011)? :The impact of the extended-entry and graduate-entry degrees on the demography of medical school applications and accepted applicants, in relation to standard-entry degrees at eighteen British medical schools

2023· other· en· W7139435810 on OpenAlexfundno aff
SIAN CAROLYNN LAWRENCE

Bibliographic record

VenueDurham e-Theses (Durham University) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersYork UniversityDurham UniversityQueen Margaret University
KeywordsDisadvantagedMedical schoolDiversity (politics)InstitutionRelation (database)
DOInot available

Abstract

fetched live from OpenAlex

In 1997, the MWASC reported a lack of diversity amongst undergraduate medical students. Three years later, four-year Graduate-entry (GEM) degrees were introduced, followed by six-year Extended-entry degrees in 2001. These had a widening access remit, with EXT degrees using contextual admissions to attract students from disadvantaged backgrounds and GEM degrees providing a 'second chance' for mature students with a degree to study medicine. This quantitative research utilised the novel approach of FOI requests to obtain secondary data relating to applications and admissions at the eighteen British medical schools which ran EXT and/or GEM degrees alongside pre-existing Standard-entry (STN) medical degrees between 2002 and 2011. Using three independent variables (NS-SEC, POLAR and last institution attended) applications and admissions to the EXT and GEM degrees have been explored in relation to STN degrees, to ascertain if they have fulfilled their widening access remit.

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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0010.005
Scholarly communication0.0010.001
Open science0.0050.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.000

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 head0.019
GPT teacher head0.275
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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