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Record W1552108110 · doi:10.1111/capa.12104

Performance measurement in Canadian employment service delivery, 1996‐2000

2015· article· en· W1552108110 on OpenAlexaffabout
John Grundy

Bibliographic record

VenueCanadian Public Administration · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsGovernmentalityScholarshipAccountabilityArgument (complex analysis)Performance measurementGovernment (linguistics)Corporate governanceSociologyService delivery frameworkService (business)Neoliberalism (international relations)Public administrationPolitical sciencePublic relationsBusinessEconomicsSocial scienceManagementLawMarketingPolitics

Abstract

fetched live from OpenAlex

Abstract This article draws on the theoretical insights of Foucauldian governmentality scholarship to analyze a performance measurement system developed by the federal government in the 1990s to assess employment services for the unemployed. An examination of Human Resource Development Canada's Results‐Based Accountability Framework yields insights into contestation and incoherence in performance measurement, often overlooked in governmentality research. This argument is developed by detailing three obstacles to implementing the performance measurement system: dilemmas of technical coordination, contestation by actors invested in different terms of measurement, and widespread recognition of the ambiguities of the performance data. The paper concludes by calling for more variegated accounts of governance in governmentality scholarship.

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)0.009
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.333
Threshold uncertainty score0.774

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.021
Science and technology studies0.0060.002
Scholarly communication0.0040.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.117
GPT teacher head0.310
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2015
Admission routes2
Has abstractyes

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