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Record W1969891464 · doi:10.1108/00251740310496279

The use of multilevel performance indicators in managing performance in health care organizations

2003· article· en· W1969891464 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueManagement Decision · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsUniversité de MontréalUniversity of Toronto
Fundersnot available
KeywordsRationalityAccountabilityConstruct (python library)LegitimacyInstitutional theoryBusinessOrganizational performanceDual (grammatical number)Process (computing)Performance measurementAccreditationHealth carePerformance indicatorOrganizational culturePublic relationsPsychologyMarketingPolitical scienceEconomicsManagementPoliticsComputer scienceEconomic growth

Abstract

fetched live from OpenAlex

The performance construct may be one of the most elusive in organization theory. Health care organizations are particularly complex owing to their dual lines of accountability, i.e. professional and administrative. This article examines the factors affecting performance indicator development and use at the technical/managerial and institutional levels, including the accreditation process and the relationship between levels. Using institutional and rational/goal theory, the motivations behind performance measurement behavior at different organizational levels was explored. Results show that the institutional level is motivated by legitimacy while the technical/managerial level is motivated by rationality. Tensions exist between the two levels and between indicator development and use.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.224
Teacher spread0.209 · 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