Ecological Modernization And The Limits Of Environmental Accounting?
Bibliographic record
Abstract
In the marketplace of ideas the discourse of ecological modernization— with its emphasis on win‐win solutions, the need for universal regulation and appeals to science—has been popular of late. Environmental accounting (EA) literatures have not been immune to the attractions of ecological modernization ideas. The strategic positioning of EA research within the discourse of ecological modernization has undoubtedly provided EA with much needed visibility and legitimacy within the academic community, and has likely encouraged corporations to ‘support’ (both in financial and ideological terms) the work of EA. Yet this discourse may ultimately be limiting. In this critical commentary we propose that the ‘ideological effect’ of ecological modernization is such that the intersection of ecological and social realms is ignored and issues of social justice are effectively erased, despite this discourse’s ‘radical’ or ‘critical’ aspirations. In other words, ecological modernization is a discourse of the status quo. Overall, EA’s harmonization with this discourse has the (un)intended effect of convincing us that the system is working, that ‘progress is being made.’ This distracts us from asking difficult questions regarding the role of environmental accounting in perpetuating unequal and exploitative social relations.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.045 |
| Scholarly communication | 0.017 | 0.024 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".