Coaching Extremely Normal Clients in Professional Services Firms: Contemptuous and Compassionate Perspectives from Philosophy and Psychoanalysis
Bibliographic record
Abstract
In this paper, I investigate my experience coaching extremely normal clients in a leading professional services firm. I contextualize my experience with insights from philosophical and psychoanalytic writing on normalcy, contrasting a contemptuous view of normalcy in the writings of Nietzsche and de Boton with a more compassionate understanding of normalcy in the writing of Christopher Bollas. I explore Bollas’ concept of ‘normotic illness,’ which he contrasts with psychotic illness, with the latter representing a loss of objectivity, and the former a loss of subjectivity. I conclude with recommendations on how to coach the overly normal using 360 assessments and follow up coaching that emphasizes the importance of authenticity, self-reflection and individuality in leadership effectiveness. I conclude with a reflection on the differing roles philosophy and psychoanalysis might play more generally in human development processes.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.053 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".