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Record W3165270591

Survey of students' perception of the jurisprudence, ethics and business management course at the Canadian Memorial Chiropractic College.

2021· article· en· W3165270591 on OpenAlexaffabout
Brian J Gleberzon

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticLikert scaleMedical educationHumanitiesLibrary sciencePsychologyMedicineArtAlternative medicineComputer science
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: The objective of this study was to survey 2018-2019 Year III students at the Canadian Memorial Chiropractic College in order explore their perceptions of the components of the revised Jurisprudence, Ethics and Business Management course. METHODS: This study was approved by the Research Ethics Board. A paper survey was distributed to all enrolled students. Using a five-point Likert scale, students were asked if they perceived the course material was (i) well-presented and (ii) important for them to know as future chiropractors. Students were required to sign a consent form to participate. RESULTS: Survey response rate was 94%. Over 90% of respondents 'strongly agreed/'agreed' lectures, small group session and course assignments were well presented and important for them to know as future chiropractors. Respondents were more critical of the online business modules (on average, 50% 'strongly agreed/agreed'). CONCLUSIONS: The information from this survey will enable refinement of future versions of this course.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.215
GPT teacher head0.412
Teacher spread0.197 · 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 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

Citations2
Published2021
Admission routes2
Has abstractyes

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