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Record W1540716080 · doi:10.1108/09513550410530144

Performance measurement and adoption of balanced scorecards

2004· article· en· W1540716080 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Public Sector Management · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBalanced scorecardRespondentBusinessAccountabilityGovernment (linguistics)Performance measurementAccountingProfit (economics)Performance managementQuality (philosophy)Process managementMarketingEconomicsPolitical science

Abstract

fetched live from OpenAlex

To deal with financial constraints and increasing demand on accountability, government administrators have begun implementing modern management tools in their organizations. The balanced scorecard, a performance and strategic management system, has been adopted in for‐profit organizations with success and its application in the government sector is explored in this study. Results of a survey of municipal governments in the USA and Canada show that there is limited use of the balanced scorecard. Most municipal governments, however, have developed measures to assess their organizations' financial, customer satisfaction, operating efficiency, innovation and change, and employee performance. Respondent administrators, in general, have confidence in the quality of the performance measures and about half reported that these measures were used to support various management functions. The respondent administrators also have a good understanding of the balanced scorecard and the implementers are positive about their experience.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.026
GPT teacher head0.212
Teacher spread0.186 · 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