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Adaptive practices of healthcare workers under the reforms

2022· article· en· W4303940267 on OpenAlexaboutno aff
Larisa V. Temnova, E. G. Bapinaeva

Bibliographic record

VenueRUDN Journal of Sociology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsnot available
Fundersnot available
KeywordsResistance (ecology)Health careAdaptation (eye)Unconscious mindPsychologyService (business)NursingPublic relationsMedicinePolitical scienceBusinessLawMarketing

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.671
GPT teacher head0.588
Teacher spread0.083 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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