Deprofessionalisation as a Performance Management Dysfunction: The Case of Inclusive Education Teachers in Russia
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.
Bibliographic record
Abstract
This article examines two important phenomena related to the performance-based assessment challenges of the teaching profession: deprofessionalisation and dealtruisation. Theoretical analyses have allowed us to draw conclusions concerning the trends in the teaching profession, its relations with dealtrusation and deprofessionalisation, and the various contradictions associated with the performance of professionals in their social role during performance-based reforms. Based on Merton’s methodology of altruism research—and partly debating with modern approaches to deprofessionalisation—we have chosen inclusive education teachers as a special group, which under the influence of dysfunctional performance management requirements became dealtruistic to the greatest extent. In this study, convenience sampling and in-depth interviews have been used. The sample consisted of 57 inclusive education teachers. Data processing was carried out with the use of Corpus Tool 3.1.14. As a result, based on the typology of altruistic behaviour, as introduced by Merton, we have identified the type of behaviour amongst teachers, which leads us to the formulation of educational and school policy recommendations. The authors suggest that a more in-depth study of the experience of other countries will help with the development of a more optimal version of educational reforms and its continuation.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it