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Record W2170455131 · doi:10.1108/jhom-06-2014-0101

Culture and cognition in health systems change

2015· article· en· W2170455131 on OpenAlexaff
Jenna M. Evans, G. Ross Baker, Whitney Berta, Jan Barnsley

Bibliographic record

VenueJournal of Health Organization and Management · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCognitionValue (mathematics)Scale (ratio)Theory of changeCulture changeProcess (computing)Change management (ITSM)Action (physics)Organizational changeOrganizational cultureKnowledge managementPsychologySociologyPublic relationsComputer scienceSocial sciencePolitical scienceBusiness

Abstract

fetched live from OpenAlex

PURPOSE: Large-scale change involves modifying not only the structures and functions of multiple organizations, but also the mindsets and behaviours of diverse stakeholders. This paper focuses on the latter: the informal, less visible, and often neglected psychological and social factors implicated in change efforts. The purpose of this paper is to differentiate between the concepts of organizational culture and mental models, to argue for the value of applying a shared mental models (SMM) framework to large-scale change, and to suggest directions for future research. DESIGN/METHODOLOGY/APPROACH: The authors provide an overview of SMM theory and use it to explore the dynamic relationship between culture and cognition. The contributions and limitations of the theory to change efforts are also discussed. FINDINGS: Culture and cognition are complementary perspectives, providing insight into two different levels of the change process. SMM theory draws attention to important questions that add value to existing perspectives on large-scale change. The authors outline these questions for future research and argue that research and practice in this domain may be best served by focusing less on the potentially narrow goal of "achieving consensus" and more on identifying, understanding, and managing cognitive convergences and divergences as part of broader research and change management programmes. ORIGINALITY/VALUE: Drawing from both cultural and cognitive paradigms can provide researchers with a more complete picture of the processes by which coordinated action are achieved in complex change initiatives in the healthcare domain.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

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

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 head0.064
GPT teacher head0.276
Teacher spread0.212 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2015
Admission routes1
Has abstractyes

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