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Record W2886101633 · doi:10.1177/0021886318795391

Individual Cognitive Effort and Cognitive Transition During Organization Development

2018· article· en· W2886101633 on OpenAlexaff
Philip J. Maxton, Gervase R. Bushe

Bibliographic record

VenueThe Journal of Applied Behavioral Science · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAppreciative Inquiry and Organizational Change
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAppreciative inquiryCognitionIntervention (counseling)PsychologySet (abstract data type)Psychological interventionProcess (computing)Transition (genetics)Order (exchange)Developmental psychologySocial psychologyCognitive psychologyPsychotherapistBusinessComputer science

Abstract

fetched live from OpenAlex

How do personal mind-sets change during an organization development intervention and how are these transitions associated with the intervention characteristics? In a qualitative theory-driven case study based in South Africa, the transitions of six individuals during an appreciative inquiry were scrutinized longitudinally for first-order and second-order changes. Five individuals showed first-order changes and two showed second-order changes. The engaging and emergent characteristic of the intervention explained the majority of these cognitive transitions. A third type of change in mind-set emerged in four of the cases: the development of an appreciative stance, which we classify as a form of cognitive effort rather than a cognitive transition. We conclude that interventions focusing on positivity may lead to participants developing an appreciative stance, but successful organization development might not occur without sufficient engagement in an emergent process. We provide some guidelines for practitioners for conducting an engaging emergent change process.

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)0.009
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.032
GPT teacher head0.264
Teacher spread0.232 · 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 designObservational
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

Citations10
Published2018
Admission routes1
Has abstractyes

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Same venueThe Journal of Applied Behavioral ScienceSame topicAppreciative Inquiry and Organizational ChangeFrench-language works237,207