規模を拡大する前に政策に基づく証拠を最適に生成する
John A List1,2,3
1The University of Chicago, Chicago, IL, USA. jlist@uchicago.edu.
Nature
|February 15, 2024
まとめ
政策のスケーリングを改善するには,必要な情報といつかを尋ねることによって,最適な証拠を生成します. スケールサイエンスに基づいたこのアプローチは,
科学分野:
- 社会科学
- 行動経済学
- 政策の実施
背景:
- 社会的介入の規模を拡大すると,コスト・ベネフィット・プロファイルが低下する"電圧の低下"が起こります.
- 効果的な政策拡大は コミュニティの健康と安全 そして将来の機会に不可欠です
研究 の 目的:
- 政策に基づくエビデンスを生み出すための最適な戦略を提案し,スケーリング"電圧の低下"を軽減する.
- 社会科学の研究モデルを 拡張科学の要求に合わせて再構築する
主な方法:
- 伝統的な研究モデルに変化を促す
- 発見段階での統合されたスケールテストによる有効性試験の増強
主要な成果:
- 最適な証拠生成には,必要な情報とその順番を定義する必要があります.
- スケールテストを早期に統合すると,スケール信頼要件の"全体像"が認識されます.
結論:
- 伝統的な研究モデルを逆転させれば 政策のスケーリング"電圧の低下"を減らすことができます
- 政策の成功の鍵となるのは,当初から規模を考慮した証拠の生成を優先することだ.
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