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Record W4409509765 · doi:10.1002/sd.3480

Management Responses to Climate Change: An Analysis of Scholarly Recommendations

2025· article· en· W4409509765 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSustainable Development · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversité Laval
FundersDeutscher Akademischer Austauschdienst
KeywordsClimate changeEnvironmental resource managementEnvironmental planningNatural resource economicsPolitical scienceEnvironmental scienceEconomicsEcologyBiology

Abstract

fetched live from OpenAlex

ABSTRACT This article analyzes management scholars' recommendations for business managers on how to respond to climate change. It distinguishes recommendations by whether they propose responsiveness to climate change that aims for adaptation, mitigation, and resilience as short‐term orientations as well as transformation and regeneration as long‐term orientations. The analysis of 192 practical implications in 91 articles suggests that managers are recommended to make short‐term oriented adjustments to their business by adapting to the challenges and contributing to the mitigation of greenhouse gas emissions. There are fewer recommendations on what measures managers should take to make businesses more resilient to the effects of climate change, how managers should contribute to the transformational needs of society, and how business models could be designed that support long‐term climate mitigation. The article provides an overview of the recommendations in the reviewed social scientific management literature and discusses further avenues for understanding and advancing the role of business toward climate‐friendly markets and society.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.237
GPT teacher head0.463
Teacher spread0.226 · 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