MétaCan
Menu
Back to cohort
Record W4391734244 · doi:10.53935/jomw.v2021i1.138

Key Drivers of Culture Change in Organizations

2021· article· en· W4391734244 on OpenAlexaff
Dominique Tremblay

Bibliographic record

VenueJournal of Management World · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsKey (lock)BusinessOrganizational cultureProcess managementCulture changeKnowledge managementPolitical scienceComputer sciencePublic relationsSociologyComputer securityAnthropology

Abstract

fetched live from OpenAlex

The current study was designed to identify and test the key drivers of culture change in public service organizations. This is a rare multi-organization empirical study that examined the impact of seven key change drivers on changes in culture. The seven independent variables in the research model are all hypothesized to be directly associated with the dependent variable of organizational culture change. The results of this research suggest that changes in leadership personnel and changes in human resources practices should be priorities for those embarking on a culture change initiative. Organizational leaders and managers who understand the importance of these change drivers, and who implement them properly, should experience more frequent success in their culture change initiatives. This study contributes to the literature on organizational culture and sustainability by highlighting the importance of the alignment of competing cultural values in the face of sustainability challenges.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0040.004
Scholarly communication0.0080.004
Open science0.0010.006
Research integrity0.0010.002
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 head0.020
GPT teacher head0.228
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Management WorldSame topicOrganizational Learning and LeadershipFrench-language works237,207