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Addressing Attribution through Contribution Analysis: Using Performance Measures Sensibly

2001· article· en· 342 citations· W2113515522 on OpenAlex· 10.3138/cjpe.016.001

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian venueIt was published in a Canadian venue.

Full frame distilled prediction

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.

Candidate categories
Insufficient payload (model declined to judge)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Simulation or modelingConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.674
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.680
GPT teacher head0.570
Teacher spread
0.109 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Abstract: The changing culture of public administration involves accountability for results and outcomes. This article suggests that performance measurement can address such attribution questions. Contribution analysis has a major role to play in helping managers, researchers, and policymakers to arrive at conclusions about the contribution their program has made to particular outcomes. The article describes the steps necessary to produce a credible contribution story.

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.

The record

Venue
Canadian Journal of Program Evaluation
Topic
Evaluation and Performance Assessment
Field
Decision Sciences
Canadian institutions
Government of Canada
Funders
not available
Keywords
AttributionAccountabilityAuthorship attributionPublic relationsAdministration (probate law)PsychologyBusinessPolitical scienceSocial psychologyComputer scienceLawArtificial intelligence
Has abstract in OpenAlex
yes