PART: An Attempt in Federal Performance-Based Budgeting
Notice bibliographique
Résumé
ABSTRACTThe Program Assessment Rating Tool (PART) was the most recent attempt in U.S. federal performance-based budgeting innovations. This article investigates the development and implementation of the PART in the federal budgeting process. Over 1000 PART reports from 2004 to 2008 were retrieved from the PART official website. The effects of the PART ratings are examined in a set of regression models with a group of control variables that are known to influence federal budget decisions. The models show positive, but not statistically significant, results. Therefore, not enough empirical evidence is found that program appropriation was impacted the PART ratings.Keywords: PART, performance-based budgeting, normative budget theory, measurement.IntroductionPerformance-based budgeting is nothing new in public sectors. It derives from a very simple question - why spend limited funds on some programs or organizations when the measures reveal that other programs or organizations are more effective at achieving the political objectives behind the budget's macro allocations? The historical development of performance-based budgets includes a series of four major government-wide budgeting initiatives attempted since World War II: the Budget and Accounting Procedures Act of 1950, the Planning-Programming-Budgeting System implemented in 1965, Management Objectives initiated in 1973, and Zero-Based Budgeting initiated in 1977. Each was an analytical technique that embraced one of the major management concepts of its era with the goal of improving the quality and the influence of policy decisions. However, all of the reforms were insular, begun and conducted the executive branch with Congress given no role and the public screened from view (U.S. General Accounting Office, 1997). Such reforms generally did not carry over from one presidential administration to the next.Federal efforts in rationalizing budget decisions the intervening decades resulted in the Program Assessment Rating Tool (PART) under the President's Management Agenda's budget and integration initiative (Kettl, 2000; U.S. General Accounting Office, 2003). The PART was designed as an effort to improve the efficiency of the federal government (see, e.g., Blanchard, 2008; Breul, 2007b; Redburn et al., 2008; Shea, 2008). But, the PART appears to appeal to a deeply entrenched desire within the public administration community to find a way to budget by performance or for (White, 2012). The PART was intended to provide a consistent system to evaluate federal programs as a part of the Presidential budget decision process (U.S. Office of Management and Budget, 2002) and sought to overcome issues in the Government Performance and Results Act implementation such as insufficient use of information in budget decisions (Dull, 2006).The PART was a questionnaire consisting of approximately 30 questions (the number varies slightly depending on the type of program being evaluated). Federal managers were required to answer these questions about their program purpose and design, strategic planning, program management, and program results. Programs were given ratings based on the answers. These ratings were weighted to a given percentage each section. The program purpose and design section was weighted to 20%, the strategic planning section was weighted to 10%, the program management was weighted to 20%, and the program results section was weighted to 50%. The ratings weighted to the given percentage were added together to produce an aggregate score that ranges from 0 to 100. This aggregate score was indicated in a qualitative rating as follows:Rating RangeEffective 85-100Moderately Effective 70-84Adequate …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,019 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».