← 論文一覧に戻る

エネルギー移行コストは誰が負担すべきか:アルバータ州における政治的イデオロギーと分配的公正

Who should pay for energy transition costs? Political ideology and distributive fairness in Alberta (原題)

Huong Thi Mai Le

Energy Research & Social Science📚 査読済 / ジャーナル2026-10-07#エネルギー転換対象セクター: power
DOI: 10.1016/j.erss.2026.105010
原典: https://doi.org/10.1016/j.erss.2026.105010
📄 PDF

🤖 gxceed AI 要約

日本語

アルバータ州住民1527人への独自調査を用い、左右の政治的イデオロギーがエネルギー移行の分配的公正の認識をどう形成するかを分析した。イデオロギーの影響は普遍的ではなく選択的で、石油ガス産業への増税や移行便益の地域配分など、費用・便益を明示的に再分配する政策で最も強く現れる。他の次元は家計のエネルギー負担、地域のエネルギー依存度、制度への信頼、気候懸念とより一貫して関連する。分配的公正は移行支持の代理指標ではなく、費用配分の政治的正当性を評価する多次元的要素だと示す。

English

Using original survey data from 1,527 Alberta residents, this study examines how left-right ideology shapes perceptions of distributive fairness in energy transition across four dimensions: funding mechanisms, cost responsibility, and regional distribution of costs and benefits. Ideological effects are selective, strongest where policies explicitly redistribute costs or benefits, such as higher oil and gas taxes and regional benefit allocation. Other dimensions track household energy burden, local energy dependence, institutional confidence, and climate concern. Distributive fairness emerges as a distinct, multidimensional driver of transition legitimacy and durability.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本でもGX推進の負担配分(炭素賦課、電気料金、地域間格差)は政治的争点化しつつあり、脱炭素政策の社会的受容性と「公正な移行」を設計する上での示唆がある。SSBJ開示やトランジション・ファイナンスの議論でも、費用負担の公平性は投資家・政策立案者の関心と接続する。

In the global GX context

As ISSB/CSRD disclosure and transition finance expand, this paper reminds global scholars that transition durability hinges on perceived distributive fairness, not just emissions reduction. It offers a survey-based framework for measuring legitimacy of cost allocation that can inform just-transition policy design beyond Canada.

👥 読者別の含意

🔬研究者:分配的公正を多次元の世論構成概念として測定する実証枠組みを提供する。

🏢実務担当者:炭素賦課や地域配分の政策リスクを、地域社会の受容性の観点から評価する材料になる。

🏛政策担当者:移行政策の長期的耐久性には、費用負担の公平な設計と地域配分への配慮が不可欠だと示唆する。

📄 Abstract(原文)

Public support for energy transition does not necessarily imply agreement over how its costs and benefits should be distributed. As governments accelerate the transition to low-carbon energy, political conflict increasingly centers not on whether the transition should occur, but on whether its economic burdens and benefits are allocated fairly. This paper examines how left–right political ideology shapes perceptions of distributive fairness in Alberta's energy transition. Using original survey data from 1527 Alberta residents, multivariate regression models analyze four dimensions of distributive fairness: funding mechanisms, responsibility for transition costs, the regional distribution of costs, and the regional distribution of benefits. The findings show that political ideology exerts selective rather than universal effects. Ideological differences are strongest when policies explicitly redistribute economic costs or benefits, particularly through higher taxes on the oil and gas industry and the regional distribution of transition benefits. By contrast, other dimensions of distributive fairness are more consistently associated with household energy burden, local energy dependence, institutional confidence, climate concern, and broader political value orientations. These findings demonstrate that distributive fairness is a distinct and multidimensional aspect of public opinion, with different distributive questions activating different political and contextual considerations. Rather than serving simply as a proxy for support for energy transition, distributive fairness reflects how citizens evaluate the political legitimacy of allocating transition costs and benefits. The study suggests that the long-term political durability of energy transition depends not only on reducing emissions but also on designing policies that citizens perceive as distributively fair.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。