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Record W2112597106 · doi:10.1177/0021886300364003

Multiple Imaginings of Institutional Identity

2000· article· en· W2112597106 on OpenAlexaff
Julia Harrison

Bibliographic record

VenueThe Journal of Applied Behavioral Science · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsTrent University
Fundersnot available
KeywordsInstitutionSociologyLoyaltyTotal institutionIdentity (music)The ImaginaryPerspective (graphical)Gender studiesPsychoanalysisSocial psychologySocial sciencePsychologyAestheticsLawPolitical science

Abstract

fetched live from OpenAlex

In 1996-1997, the author conducted research at the Hanson Institute of Psychiatry, a large psychiatric research hospital in a North American city. The author came to understand that there was a desire on the part of some senior managers to cultivate a loyalty and a sense of responsibility among staff to a singular institutional identity. This issue frames this article, drawing on anthropological understandings of the idea of culture, Martin’s fragmentation model, Maffesoli’s ideas of the social imaginary, and Goffman’s discussion of the individual perspective of an organization from “in the cracks.” The author discusses the nested imaginings that any individual would have if one considers the institutional; professional, departmental, or occupational; and individual imaginaries that fuelled employees’ ideas of the institution. There could be no real imagining of “the Hanson” because individuals imagined they worked for “a Hanson,” each imagining a slightly different institution from “in the cracks.”

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)0.012
metaresearch head score (Gemma)0.013
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 score0.017
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0110.062
Scholarly communication0.0170.029
Open science0.0020.015
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.254
Teacher spread0.234 · 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
Published2000
Admission routes1
Has abstractyes

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