Bibliographic record
Abstract
Purpose Despite its growing popularity in applied settings, executive coaching has to date received little attention in empirical research, especially in regard to the coaching process. This paper aims to investigate the effect of working alliance rating discrepancies on the development of coachees' self‐efficacy, a key outcome in leadership development. Design/methodology/approach The paper reports on a pre‐ post‐test study of a leadership development program taking place in a large North American manufacturing company. Data were collected from two samples: managers receiving coaching over an eight‐month period and internal certified coaches. In total, 30 coach‐coachee dyads were analyzed. Findings Results from an analysis of covariance did not support the authors' hypothesis, by indicating that coachees having worked with a coach who underestimated the working alliance, in relation to his or her coachee, experienced more growth in self‐efficacy than coachees who worked with a coach who either accurately estimated or overestimated the working alliance. Practical implications The results sugges that coaches should coach with an “ongoing and deliberately maintained doubt as their only certainty”. The importance for coaches to be sensitive to signs of what the coachee is experiencing, and to take the initiative to verify the coachee's comfort level with the way coaching is proceeding is addressed. Originality/value This study intended to delve deeper into the complexities of the coaching process by linking a key coaching process variable, the relationship, to coaching outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".