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Record W4224248474 · doi:10.1177/03080226221080871

The development and psychometric properties of a measure to assess the written submission of an admissions application

2022· article· en· W4224248474 on OpenAlexaff
Jill Stier, Jill I. Cameron, Behdin Nowrouzi‐Kia, Chantel Brammer, Sara Asher, Deborah Lipszyc

Bibliographic record

VenueBritish Journal of Occupational Therapy · 2022
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsSt Joseph's Health CentreNorth York General HospitalUniversity of Toronto
Fundersnot available
KeywordsCronbach's alphaReliability (semiconductor)Discriminative modelInternal consistencyMeasure (data warehouse)CognitionTest (biology)MedicineClinical psychologyPsychologyPsychometricsApplied psychologyComputer sciencePsychiatryData miningArtificial intelligence

Abstract

fetched live from OpenAlex

Introduction: Health care programs evaluate prospective applicants using cognitive and non-cognitive criteria. The aim of this research was to develop and evaluate the psychometric properties of a measure to evaluate the non-cognitive criteria of admissions applications. Method: A Masters of Occupational Therapy Written Submission Measure (MOTWSM) was developed and evaluated over 3 phases, using applicants' written statements, resumes, and reference letters. Participants included 50 students who completed an occupational therapy program for determination of internal consistency and test-retest reliability. Additionally, 195 written submissions selected from the applicants who were admitted, waitlisted, and not admitted to the program were evaluated to determine inter-rater reliability using a two-way ANOVA. Analysis of 195 submissions using a one-way ANOVA determined the measure's discriminative validity. Findings: Results indicated test-retest reliability of 0.95 and internal consistency reliability of 0.76. Inter-rater reliability reported a Cronbach's alpha coefficient of 0.86 using a horizontal scoring method. Good discriminative validity was established. Conclusion: The MOTWSM is a reliable and valid measure that can be used to evaluate the non-cognitive criteria of admissions applications in health profession programs. Use of this measure can facilitate selection of the highest caliber of students.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.168
GPT teacher head0.392
Teacher spread0.224 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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