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Record W4401241119 · doi:10.1177/00076503241255954

Walking, Talking, or Standing Still? Climate Commitment and Performance in Publicly Listed Firms in Five Major Economies

2024· article· en· W4401241119 on OpenAlexaboutno aff
Kyle Herman, Caterina Schiavoni, Gianni Guastella

Bibliographic record

VenueBusiness & Society · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsCommitLegitimacyMandatePerspective (graphical)BusinessSample (material)Action (physics)Climate changePolitical scienceLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.260
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2024
Admission routes1
Has abstractyes

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