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Record W3108078260 · doi:10.1080/13678868.2020.1850090

Can mentoring programmes develop leadership?

2020· article· en· W3108078260 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHuman Resource Development International · 2020
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsExtant taxonLeadership developmentCareer developmentHuman resourcesNeuroleadershipEducational leadershipQualitative researchPublic relationsLeadership studiesPolitical sciencePsychologyEngineering ethicsPedagogySociologyLeadership styleEngineering

Abstract

fetched live from OpenAlex

Mentoring programmes are popular within organizations as well as educational institutions. Research has shown that mentoring can be an effective tool for employee career development broadly; however, there has been a relatively small amount of research on the effectiveness of mentoring as a tool for leadership development specifically. This paper reviews the research on mentoring relationships, leadership development programmes, and the overlap of the two. Additionally, it provides a qualitative review of the three extant longitudinal intervention studies that have explicitly evaluated the impact of mentoring programmes for leadership development. The review shows that mentoring programmes are promising arenas for developing leadership capabilities for both mentees and mentors, but more evidence is needed to reach a definitive conclusion. The article concludes with recommendations for human resource development practitioners who would like to use mentoring for leadership development purposes.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.710
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.149
GPT teacher head0.339
Teacher spread0.190 · 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