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Record W3205274928

Gender diversity in chiropractic leadership: a cross-sectional study.

2021· article· en· W3205274928 on OpenAlexaffabout
Ayla Azad, Michele Maiers, Kent Stuber, Michael Ciolfi

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsChiropracticDiversity (politics)Political sciencePrincipal (computer security)MedicineAlternative medicineLaw
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of this cross-sectional study was to compare the number of males and females in leadership positions, and whether there is a relationship between gender and degrees held in those positions, within chiropractic academic institutions, national regulatory bodies and the most widely representative national professional associations in the United States and Canada. METHODS: tests of independence were conducted to determine the relationship between gender (male vs. female) and other variables, including position (principal vs secondary), and chiropractic and other advanced professional degrees. RESULTS: A total of 107 leaders were identified across institutions and organizations. Under one-third of leaders (30.8%) were identified as female. Males were more likely to be in principal leadership roles (86.2%) and more likely to be in a secondary leadership position (62.8%). CONCLUSION: Male leaders significantly outnumber female leaders in both principal and secondary leadership positions within American and Canadian chiropractic institutions. Strategies should be developed to include gender diversity within all chiropractic organizations.

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)0.003
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 score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.519
GPT teacher head0.353
Teacher spread0.166 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

Explore more

Same venuePubMed→Same topicGender Diversity and Inequality→French-language works237,207→