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Record W2088839272 · doi:10.1177/1056492607310983

Acting at Work

2008· article· en· W2088839272 on OpenAlexaff
Flora Stormer, Kay Devine

Bibliographic record

VenueJournal of Management Inquiry · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsAthabasca UniversityUniversity of Alberta
Fundersnot available
KeywordsConformityValue (mathematics)Exploratory researchSociologySocial psychologyWork (physics)PsychologyOrder (exchange)Public relationsPolitical scienceSocial scienceBusinessComputer science

Abstract

fetched live from OpenAlex

Façades of conformity (FOC) is a theoretical concept coined to describe employees who act as if they embrace an organization's values when they really don't in order to survive and/or succeed within that organization. This exploratory study combines value theory and the sociology of the professions to explore manifestations of FOC among professionals (university faculty members). Respondents' experiences of “acting at work” reveal the presence, absence, and dynamic nature of FOC. Response patterns allow us to confirm, disconfirm, and extend Hewlin's (2003) theory by identifying two types of FOC, four issues respondents typically “façade” about, behaviors enacted during the use of FOC, and the perceived risks associated with not using FOC at work. These results have significant implications for the scholarly and managerial practice of assessing value congruence between individuals and organizations.

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)0.002
metaresearch head score (Gemma)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.050
GPT teacher head0.240
Teacher spread0.190 · 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

Citations37
Published2008
Admission routes1
Has abstractyes

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