Le suivi de la performance, de I'incantatoire au passage à I'acte:Une étude du suivi de performance de six programmes d'aide aux entreprises1
Bibliographic record
Abstract
Sommaire: Cet article étudie le suivi de la performance dans les programmes publics et exprime le potentiel que représente cet outil de gestion pour les organisations publiques. Les auteurs traitent d'une question de recherche portant sur la conformité du suivi de la performance dans les programmes sous étude pour la période 1993–1998, et des causes des écarts observés par rapport au modèle‐type de suivi de la performance. Le suivi de performance fut réaliséà cette époque de manière ad hoc et opportuniste. Leurs recherches ont permis de conclure que le suivi de performance s'est heurté d'abord à la difficulté de définir de manière univoque le concept de la « bonne » performance d'un programme. S'ensuivirent des difficultés intellectuelles et pratiques pour mesurer et évaluer ladite performance. Cependant, la difficulté de mettre en place un réel processus de suivi n'est pas imputée à cette seule cause. On observerait plutôt la convergence de plusieurs causes qui se manifestent en efforts conceptuels insuffisants, au moment de la conception et de la mise en Deuvre des programmes, pour développer et implanter un authentique suivi de la performance. Abstract: This article focuses on performance monitoring in public programs and demonstrates the potential this management tool has for public organizations. The authors examine studies dealing with the consistency of performance monitoring during the period 1993 to 1998 for the programs under review, and the reasons for the differences observed when compared with the standard model for performance monitoring. During this period, performance monitoring was done on an ad hoc and opportunistic basis. Based on their research, the authors conclude that the first obstacle to performance monitoring is the difficulty of defining, unequivocally, the concept of “good” performance with reference to a program, as well as the intellectual and practical difficulties of measuring and evaluating the said performance. However, this is not the only reason why implementing a real monitoring process is so difficult. Rather, it could be that the convergence of several causes at the time the programs are designed and implemented, which results in insufficient conceptual efforts to develop and establish an authentic performance monitoring process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".