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A team emergent state approach towards readiness to change

2021· article· en· W3185021300 on OpenAlexaff
Patrick Michel Groulx, Kevin Johnson, Jean‐François Harvey

Bibliographic record

VenueAcademy of Management Proceedings · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsMediationProcess (computing)ReflexivityTeam effectivenessTheory of changeProcess managementPlan (archaeology)Team buildingPsychologyOrganizational changeFoundation (evidence)Knowledge managementPolitical scienceEngineeringPublic relationsComputer scienceManagementSociologyEngineering management

Abstract

fetched live from OpenAlex

Building on the need for a team based approach towards readiness to change (Rafferty, Jimmieson & Armenakis, 2013), the authors propose and test the process by wich team readiness to change emerges. Building on the foundation of the team regulation theory and readiness to change theory, the authors propose that team reflexivity play a central role in the emergence of team readiness to change by developing a team understanding of organizational change which enables teams to plan effectively their efforts towards the implementation. In addition, in response to current debate on the effect of managers on the development of team emergent states, the authors demonstrate the negative effect of the non-implication of managers in the process of emergence. In total, 83 teams participated in this cross-sectional study providing primary support to the double mediation model of the emergence of team readiness to change.

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)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0020.005
Scholarly communication0.0050.005
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.161
GPT teacher head0.381
Teacher spread0.220 · 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 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
Published2021
Admission routes1
Has abstractyes

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