Regulatory impact analysis: The experience of policy analysis in the Korean central government
Notice bibliographique
Résumé
Introduction Policy analysis plays a crucial role in the policymaking process, contributing to rational decision making that makes public policy more efficient from policy formation all the way through to evaluation. The central government of Korea has been conscious of the importance of policy analysis since the 1960s, and first adopted policy analysis in 1967 alongside the Second Five-Year Economic Development Plan (1967– 71). The Economic Development Plan (EDP) was initially proposed based on the need for professional and systematic plans to tackle global economic challenges. The EDP was taken a step further through analysis and forecasts by participating foreign experts, ministries, financial institutions and other professionals under the supervision of the Economic Planning Board. However, the government-driven EDP ended in the late 1990s with the Asian financial crisis. Since then, a large chunk of analysis in the central government has given way to government-funded research institutes (Jung, 2002). Korea has adopted numerous key policy analysis systems since the late 1970s. The Environmental Impact Assessment, which began in 1977, was aimed at achieving balance between development and conservation, pursuing eco-friendly sustainable development, and creating a healthy and pleasant environment (Ministry of Environment, 2016). The Traffic Impact Assessment of 1987 was brought in to analyse and predict the effects of traffic volume, flow and safety in order to minimise traffic problems. The regulatory impact analysis (RIA) was introduced in 1998 to improve regulatory quality and curb the creation of unreasonable regulations (The Office for Government Policy Coordination, OGPC et al, 2005). The preliminary feasibility study was initiated in 1999 to review the economic and technological feasibility of large-scale government projects, to ensure the objectivity of feasibility studies and improve the efficiency of financial investment. Since the 2000s, the Gender Impact Assessment in 2002 was introduced to evaluate the socio-economic disparities between men and women in the process of establishing and implementing major policies in order to promote gender equality (Ministry of Gender Equality and Family, 2018). The Corruption Impact Assessment in 2005 was designed as an anticorruption policy by eliminating unclear laws and unrealistic regulations, promoting appropriate standards in the process of drafting and enacting laws, bringing greater transparency to administrative procedures and rationally analysing the causes of corruption (Anti-Corruption and Civil Rights Commission, 2017).
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,007 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».