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Record W2155601053 · doi:10.1177/1356389004046292

What Counts is not Falling... but Landing

2004· article· en· W2155601053 on OpenAlex
Astrid Brousselle

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEvaluation · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsDouglas Mental Health University InstituteDouglas College
FundersCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsStrengths and weaknessesProcess managementFalling (accident)Process (computing)Management scienceComputer scienceOperations researchPolitical scienceBusinessPsychologyEngineeringMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Implementation evaluations, also called process evaluations, involve studying the development of programmes, and identifying and understanding their strengths and weaknesses. Undertaking an implementation evaluation offers insights into evaluation objectives, but does not help the researcher develop a research strategy. During the implementation analysis of the UNAIDS drug access initiative in Chile, the strategic analysis model developed by Crozier and Friedberg was used. However, a major incompatibility was noted between the procedure put forward by Crozier and Friedberg and the specific characteristics of the programme being evaluated. In this article, an adapted strategic analysis model for programme evaluation is proposed.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.008

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 head0.367
GPT teacher head0.545
Teacher spread0.178 · 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