MétaCan
Menu
Back to cohort
Record W2010466277 · doi:10.1108/13527590310507462

Indelible impressions of an authentic coach

2003· article· en· W2010466277 on OpenAlexaboutno aff

Bibliographic record

VenueTeam Performance Management · 2003
Typearticle
Languageen
FieldPsychology
TopicCoaching Methods and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsApprenticeshipCoachingSimplicityAppealStyle (visual arts)ManagementQuarter (Canadian coin)PsychologyAdvertisingBusinessVisual artsPolitical scienceArtHistoryLawEconomicsPhilosophyEpistemologyArchaeology

Abstract

fetched live from OpenAlex

The article is about a coaching/mentoring style that was developed by an entrepreneur LaFay Davenport. Ms Davenport’s coaching strategy derived from the name of her business – Simply Raw Hair Designs. The name itself implies authenticity, wholesomeness. Ms Davenport has coached, mentored and led staff for over a quarter of a century using a coaching model called “sRAW” by the author. The appeal of this model is its simplicity and universal application. Many apprentices trained under her leadership have become successful entrepreneurs themselves. Repeat business of long‐time clients benchmarks her sustained success.

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)0.004
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0060.006
Scholarly communication0.0070.003
Open science0.0010.007
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.034
GPT teacher head0.356
Teacher spread0.321 · 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 designQualitative
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
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueTeam Performance ManagementSame topicCoaching Methods and ImpactFrench-language works237,207