Corporate Social Responsibility (CSR), Environmental, Social, and Governance (ESG), and Sustainability Development Goals (SDGs) as ideological apparatuses: Sustainability and the new hegemony in emerging markets
Bibliographic record
Abstract
This article critically examines the diffusion of Corporate Social Responsibility; Environmental, Social, and Governance frameworks; and the United Nations Sustainable Development Goals in emerging markets. While often presented as neutral instruments of ethical business and sustainable development, we argue that these frameworks function as Sustainability Ideological State Apparatuses that embed, naturalize, and reproduce dominant ideologies under the guise of responsible management. Drawing on theory of ideology and theory of hegemony, we show how organizations are positioned as compliant sustainability subjects, while Western-centric norms are legitimized and internalized—often at the expense of local priorities, capacities, and epistemologies. This process constitutes a form of ideological colonization, wherein global sustainability standards displace alternative models rooted in local knowledge systems. This study illustrates how small and medium-sized enterprises in the Global South resist, reinterpret, and reconfigure these frameworks through contextually grounded practices. Our analysis contributes to Management Learning by reframing sustainability as a contested space of power, knowledge, and resistance. We call for more reflexive, decolonial approaches to organizational learning that foreground local agency and critically interrogate the ideological undercurrents embedded in global sustainability discourse.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.033 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".