炭化水素の連続性から低炭素の約束へ：アラムコ2024年アラビア語サステナビリティ言説における時間性・法性・移行ナラティブ
From hydrocarbon continuity to low-carbon promise: Temporality, modality, and transition narratives in Aramco's 2024 Arabic sustainability discourse (原題)
Khalid Abdullah Alotaibi, Mahmoud Ali Kanakri, Rami Abdulatif Sa'di, Mohammad Osman Abdul Wahab
🤖 gxceed AI 要約
日本語
サウジアラムコの2024年アラビア語サステナビリティ報告書と年次報告書を対象に、時制・相・法助動詞・目標・免責事項が企業の脱炭素言説をどう構成するかを談話語用論的に分析。炭化水素は「継続」「維持」という持続的時間で、低炭素施策は2030・2035・2050年のマイルストーンで語られる二重の時間構造を明らかにする。約束の文法的一貫性は大きく異なり、完了した削減と条件付きの意図が併存する。説明責任ある誓約と願望的志向を区別する6項目のコミットメント検証法を提案する。
English
A discourse-pragmatic analysis of Saudi Aramco's 2024 Arabic sustainability and annual reports shows a dual chronology: hydrocarbon demand is framed as continuous and durable, while low-carbon initiatives are organized around 2030/2035/2050 milestones. Grammatical commitment varies widely—completed reductions sit beside conditional intentions. The paper proposes a six-part commitment test to distinguish accountable pledges from aspirational direction.
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
日本企業の統合報告書や有報でも、脱炭素目標の時制・条件表現（「目指す」「検討中」等）と実績の書き分けは開示品質の核心。本稿の談話分析手法と6項目のコミットメント検証は、SSBJ基準下での自社開示レビューや投資家向け説明の説得力評価に応用できる視点を提供する。
In the global GX context
As ISSB/CSRD push for comparable transition-plan disclosure, this paper offers a linguistic method to assess whether corporate climate pledges are grammatically accountable or merely aspirational. It complements TCFD/ISSB transition-plan guidance by operationalizing how modality and temporality shape credibility—useful for regulators and assurance providers evaluating greenwashing risk.
👥 読者別の含意
🔬研究者:企業気候言説の時制・法性分析手法とコミットメント検証フレームを、開示品質研究やグリーンウォッシング研究に応用できる。
🏢実務担当者:自社の統合報告書・サステナビリティ報告書における目標表現の時制・条件付き表現を見直し、投資家に信頼される記述に改善する指針となる。
🏛政策担当者:移行計画開示の規制設計において、約束の実効性を測る言語的指標（時制・法性・中間目標）を検討する際の参考になる。
📄 Abstract（原文）
Energy-transition discourse is built as much from time as from technology. Dates, aspect, modal verbs, targets, scenarios, and disclaimers determine whether a corporate statement describes accomplished change, ongoing work, intended investment, conditional possibility, or distant ambition. This article examines those distinctions in Saudi Aramco's official Arabic Sustainability Report 2024 and selected market, strategy, sustainability, and forward-looking sections of its Arabic Annual Report 2024. The page-bounded corpus comprises 31,457 raw tokens and 28,446 cleaned tokens across 268 layout-defined prose blocks and 1,114 clause units. A discourse-pragmatic analysis distinguishes completed action, continuing process, dated commitment, volitional intention, predictive possibility, and cautionary qualification. It then traces how these temporal forms are assembled into narratives of continuity and transition. The findings show a dual chronology. Hydrocarbon demand and supply are represented through durable, near-continuous time: they “continue,” “remain,” and are expected to retain importance. Lower-carbon initiatives are organized through milestones, project schedules, and ambitions extending to 2030, 2035, and 2050. The contrast does not make the latter empty, since several promises have explicit metrics, scopes, and interim dates. Yet grammatical commitment varies considerably. Completed operational reductions sit beside intentions to expand hydrocarbon-linked businesses, while technological benefits are often conditional on successful testing, market formation, and policy support. Aramco's transition narrative therefore operates through temporal layering: present continuity underwrites future experimentation, and future promise legitimates present continuity. The article proposes a six-part commitment test for distinguishing accountable corporate pledges from aspirational direction without treating either as self-evidently credible or insincere.
🔗 Provenance — このレコードを発見したソース
- openalex https://royalliteglobal.com/advanced-humanities/article/view/2881first seen 2026-10-04 04:44:37
🔔 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。