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Record W3124968327

Performance Measures and the Rationalization of Organizations

2003· article· en· W3124968327 on OpenAlexaffabout
Barbara Townley, David J. Cooper, Leslie S. Oakes

Bibliographic record

VenueSSRN Electronic Journal · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRationalization (economics)CynicismOperationalizationRationalityPositive economicsSkepticismPolitical scienceEconomicsSociologyEpistemologyManagementPoliticsLaw
DOInot available

Abstract

fetched live from OpenAlex

This article focuses on rationalization, its dimensions, the possibilities of reasoned justification in the public sphere, and the technologies that would operationalize this. It does so through an analysis of the introduction of performance measurement in the Provincial Government of Alberta, Canada. We argue that performance measurement represents twin dimensions of rationalization: the pursuit of reason in human affairs, that is, the process of bringing to light the justifications by which actions and policies are pursued; and rationalization as the increasing dominance of a means-end instrumental rationality. The article illustrates how an initial enthusiasm by managers for the performance management initiatives was replaced with scepticism and cynicism. We show how the potential for reasoned justification was frustrated in practice, through a growing disparity between a discourse of reasoned justification and the practical operationalization of mechanisms of business planning and performance measurement. The search for reasoned justification and instrumental mastery are part of the same rationalization process, and these two contradictory, but inherently connected forces are an important explanation of the dynamics of managers' responses to organizational change.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.172
Teacher spread0.168 · 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 teacher head, 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

Citations6
Published2003
Admission routes2
Has abstractyes

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