Walking, Talking, or Standing Still? Climate Commitment and Performance in Publicly Listed Firms in Five Major Economies
Bibliographic record
Abstract
Recent regulatory interventions are beginning to mandate climate disclosure in listed firms. Although compelling, prior studies demonstrate that firms can symbolically commit to climate and environmental disclosures yet not undertake action. Neo-institutional theory (NIT) suggests that two strategies exist: the legitimacy perspective, which manifests in symbolic efforts, and the efficiency perspective, which is more consistent with substantive efforts. In this article, we apply NIT to assess the climate transition efforts in large, publicly traded firms in five countries with similar regulatory and economic profiles (Australia, Canada, New Zealand, the United Kingdom, and the United States). We gauge climate efforts by membership in corporate climate initiatives (CCIs) and the integration of climate action plans (CAPs). Of the eight CCIs and three CAPs investigated, we find that only two CCIs and one CAP help to improve emissions performance. The majority of firms in our sample, therefore, demonstrate the legitimacy perspective of NIT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".