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Record W2947626567

Examining the Relationship Between Peer Athlete Mentor Leadership behaviours and protégé receipt of mentoring functions

2013· article· en· W2947626567 on OpenAlexaff
Matt D. Hoffmann, Todd M. Loughead

Bibliographic record

VenueJournal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository) · 2013
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPsychologyTransactional leadershipTransformational leadershipCoachingPsychosocialAthletesProtégéSocial psychologyApplied psychology
DOInot available

Abstract

fetched live from OpenAlex

Mentoring is a process in which a more experienced and knowledgeable individual (the mentor) acts as a role model, provides support and guidance to a developing novice (the protege), and assists in that person’s development (Weaver & Chelladurai, 1999). In organizational settings, research has shown that mentors support their proteges using two types of mentoring functions: vocational and psychosocial (Kram, 1980). Further, research has indicated that mentor transformational and transactional leadership behaviours positively influence protege receipt of these two mentoring functions (Sosik & Godshalk, 2000). There are no known studies investigating the peer-to-peer mentoring that occurs between athletes in sport teams. Thus, the present study examined the relationship between peer athlete mentor leadership behaviours and protege receipt of mentoring functions. Varsity athletes (N = 272) assessed their mentor’s use of transformational and transactional leadership behaviours, and mentoring functions. Using SEM, the results showed the leadership behaviours of inspirational motivation (β = .69, p < .001), democratic behaviour (β = .32, p < .001), social support (β = .29, p < .001), and positive feedback (β = .27, p < .001) were positively related to psychosocial mentoring.  Furthermore, the leadership behaviours of intellectual stimulation (β = .51, p < .001), contingent reward (β = .22, p < .005), training and instruction (β = .64, p < .001), and social support (β = .18, p < .001) were positively associated to vocational mentoring. Practical implications of the results are discussed.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.027
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.085
GPT teacher head0.294
Teacher spread0.210 · 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 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
Published2013
Admission routes1
Has abstractyes

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