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Record W1880710745 · doi:10.1002/cjas.1317

Organizing a precarious black box: An actor‐network account of the Atlantic Schools of Business, 1980–2006

2015· article· en· W1880710745 on OpenAlexaffvenue
Ryan T. MacNeil, Albert J. Mills

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsAcadia University
Fundersnot available
KeywordsEthnographySociologySocial network analysisBlack boxActor–network theoryQualitative propertyQualitative analysisQualitative researchKnowledge managementCriminologyPublic relationsSocial scienceComputer sciencePolitical scienceArtificial intelligenceAnthropologySocial capital

Abstract

fetched live from OpenAlex

Abstract There is a growing use of actor‐network theory (ANT) throughout management and organization studies. While earlier ANT research used ethnography to “follow the actors” in the production of organization/knowledge, more recent studies use archival sources to examine developments over time. We extend the latter approach using qualitative social network analysis (SNA) and apply this to a case study of the Atlantic Schools of Business (ASB). Our contribution is two‐fold: first, through an examination of actors in the ASB networking processes over 26 years, we demonstrate how the seemingly stable surface of an organization can hide the precariousness of organizing; second, we reveal the potential fusion of ANT with SNA as a method for dealing with large qualitative datasets over long periods of time. Copyright © 2015 ASAC. Published by John Wiley & Sons, Ltd.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0050.005
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.081
GPT teacher head0.274
Teacher spread0.193 · 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.

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

Citations4
Published2015
Admission routes2
Has abstractyes

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