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Record W2132847190 · doi:10.1002/piq.21175

The Influence of Coaching on Employee Performance: Results From Two International Quantitative Studies

2014· article· en· W2132847190 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePerformance Improvement Quarterly · 2014
Typearticle
Languageen
FieldPsychology
TopicCoaching Methods and Impact
Canadian institutionsUniversité de SherbrookeLakehead University
Fundersnot available
KeywordsCoachingVariance (accounting)Empirical researchService (business)Empirical evidenceBusinessField (mathematics)MarketingPsychologyPublic relationsAccountingPolitical science

Abstract

fetched live from OpenAlex

Coaching has been identified as a key managerial behavior that organizations must promote to develop employees and achieve higher levels of performance. Despite this agreement and an increasing interest in coaching, there is still a paucity of studies exploring the impact of coaching on individual performance. This article presents an empirical investigation from two international field studies, one using business-to-business salespersons working in Latin America and the other one using business-to-consumer frontline employees from a service organization in Canada. Building on leader-member exchange theory, we propose that coaching increases individual performance beyond the potential impact of sales experience and tenure. We find that coaching can explain between 2.9% and 6.2% of the variance in performance when controlling for tenure and experience. This article makes several scientific and managerial contributions, and also opens new avenues for research.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.046
GPT teacher head0.388
Teacher spread0.342 · 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