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Record W7134824918 · doi:10.26181/13258235

Engaging Professionals in Sustainable Workplace Innovation: Medical Doctors and Institutional Work

2020· article· W7134824918 on OpenAlexaboutno aff

Bibliographic record

VenueLa Trobe University · 2020
Typearticle
Language
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Power (physics)Senior managementOrganizational cultureProcess (computing)Quality (philosophy)UnpackingQualitative research

Abstract

fetched live from OpenAlex

© 2018 The Authors. British Journal of Management published by John Wiley & Sons Ltd on behalf of British Academy of Management This paper investigates the role of medical professionals in the success and longevity of the implementation of workplace innovation and organizational change in the Accident and Emergency (A&E) Departments of two large public hospitals, in Australia and Canada, during the introduction of process improvement using Lean Management (LM) methodologies. We ask why and how doctors resist, influence or enable LM initiatives in healthcare. Using a qualitative methodology, we contribute to institutional work theory by unpacking the complex forms of boundary and practice work undertaken by key actors who effectively use their professional status and power to enable practice changes to be embedded. Our findings lend support to the importance of the involvement and ownership of senior doctors in the design, introduction and implementation of successful workplace innovation and organizational change. Senior doctors use their professional expertise, positional and political power at the industry, organization and workplace levels to influence strategically the use of resources designated for workplace innovation to improve efficiencies, quality of patient care and maintain their dominance. The significant organizational change achieved reflected the ownership and leadership of the workplace innovation by senior doctors in ‘hybrid roles’ who captured the rhetoric and minimized adversarialism among key stakeholders.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.201
Teacher spread0.189 · 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 designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

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