Adaptive practices of healthcare workers under the reforms
Bibliographic record
Abstract
The theory of high modernism and the concept ‘metis’ by J. Scott identify one of the reasons for unsuccessful state reform in various areas: when preparing changes, local practical experience is often neglected, but the success of the reform as a whole may depend exactly on such knowledge. The system ignores the possible strategies of workers’ resistance to the coming changes, many of which are unconscious. The reforms in the field of healthcare, including in Russia, have shown that doctors remain the most vulnerable group affected by changes. A side effect of the ongoing reforms is the development by the professional community of doctors of certain adaptive practices aimed at adaptation to changes with the least losses for the individual and professional activity. To identify the adaptive practices of medical workers in response to the reforms and their consequences, the authors examined the available data and conducted interviews with doctors of various specialties. As a result, adaptive practices of doctors in their professional activities were systematized, and their classification was proposed: deviant/non-deviant and active/passive. Active adaptive practices prevail and are implemented in three subsystems: doctor-administration, doctor-doctor and doctor-patient. Most doctors tend to accept changes that involve adding new practices rather than changes removing traditional practices. All respondents positively assessed new technologies, but negatively assessed rigid standards that limit their professional freedom. The development of adaptive practices depends on various factors - gender, age, length of service, specialization, position. Such practices help doctors to keep the habitual way of professional life and to adapt to new working conditions.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".