MétaCan
Menu
Back to cohort
Record W2913533742 · doi:10.1123/jsm.2018-0100

Outcomes of Mentoring Relationships Among Sport Management Faculty: Application of a Theoretical Framework

2019· article· en· W2913533742 on OpenAlexaboutno aff
Amy Baker, Mary A. Hums, Yoseph Mamo, Damon P. S. Andrew

Bibliographic record

VenueJournal of Sport Management · 2019
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsnot available
Fundersnot available
KeywordsMentorshipContext (archaeology)Sport managementPerceptionPsychologyMedical educationPublic relationsPolitical scienceMedicine

Abstract

fetched live from OpenAlex

The importance of mentoring in the development of individual careers is noted in the business and higher education literature. However, prior research has given little attention to the development of mentoring relationships between junior and senior sport management faculty members. In addition to providing context-specific information, mentorship studies of sport management faculty provide insight on an emerging and gender-imbalanced discipline in the academy. This study reviews the literature on mentorship, and presents a hybrid framework on the mentor–protégé relationships established in the academic field of sport management. Specifically, the study identifies aspects of the relationships likely to yield positive perceptual outcomes, such as relationship effectiveness, trust, and job satisfaction. Data were collected from 161 sport management faculty members in the United States and Canada. The results provide support for the new hybrid framework and highlight mentoring as a valuable mechanism to support sport management faculty.

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)0.009
metaresearch head score (Gemma)0.033
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 score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.318
Teacher spread0.293 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sport ManagementSame topicMentoring and Academic DevelopmentFrench-language works237,207