What Happens to Educational Administration When Organization Trumps Ethics
Bibliographic record
Abstract
ABSTRACT. The managerial strategies of governance prevalent in the private sector have become more and more normalized within educational institutions. These strategies, according to Dutch philosopher Zygmund Bauman, are denial of proximity, effacement of face, and reduction to traits. This article describes these managerial tactics within an educational context and unearths four systemic conditions that give rise to these strategies. These conditions are: the imperative of efficiency, diffusion of responsibility, obscurity of cause, and simplification of solutions. Various narratives are offered to demonstrate the effects of these conditions on the practice of educational administration. QUAND L'ORGANISATION PREND LE DESSOUS SUR L'ETHIQUE : QU'EST CE QUI ARRIVE A L'ADMINISTRATION EN MILIEU D'EDUCATION? RESUME. Les strategies de gestion employees frequemment dans le secteur prive pour gouverner sont devenues de plus en plus normalisees dans nos institutions scolaires. D'apres Zygmund Bauman, le philosophe neerlandais, ces strategies s'identifient comme suit: negation de la proximite (denial of proximity) effacement du visage (effacement of face) et reduction aux traits simples (reduction ta traits). Le present article decrit ces tactiques gestionnaires dans le cadre du milieu d'education et revele quatre conditions systemiques qui occasionnent l'apparition de ces strategies. Les quatre conditions sont: l'imperatif de l'efficacite, (the imperative of efficiency), la responsabilite dispersee (diffusion of responsibility), l'obscurite des cause (obscurity of cause), et la simplification des solutions (simplification of solutions). L'article offre des narrations variees pour demontrer les effets de ces conditions sur les pratiques administratives en milieu scolaire.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.048 |
| Scholarly communication | 0.022 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".