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Record W4386752929 · doi:10.1111/emre.12604

Beyond acquiescence and compromise: Organizational strategies in pluralizing institutional environments

2023· article· en· W4386752929 on OpenAlexaff
Han Dahlmans, Tobias Goessling, Patrick Kenis

Bibliographic record

VenueEuropean Management Review · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsAcquiescenceCompromiseVariety (cybernetics)Set (abstract data type)Public relationsBusinessPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Abstract We set out to investigate how organizations respond to the variety of requirements as experienced in their pluralizing institutional environments. We found that, in addition to acquiescence and compromise, Dutch vocational education and training (VET) organizations predominantly respond with cooperation and coordination strategies. Extensive multistage qualitative data analysis of 26 semi‐structured in‐depth interviews with management team (MT) members showed that cooperation and coordination are viable and effective response strategies to face a divergent and highly differentiated set of sometimes‐conflicting institutional requirements. Our study advances understanding of how organizations deploy strategic choice to arrive at their strategic responses. It offers organizational leaders, legislators, policymakers, and other constituents' insights into complex reality of how contemporary organizations actually relate to and act in their pluralizing institutional environments.

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)0.022
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 score0.022
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.019
Scholarly communication0.0110.008
Open science0.0020.009
Research integrity0.0020.002
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 head0.016
GPT teacher head0.221
Teacher spread0.204 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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