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Record W3180156356

Organizational (issue) Field Perspective on Climate Change

2021· article· en· W3180156356 on OpenAlexaff
Achim Oberg, Lianne Lefsrud

Bibliographic record

VenueCBS Research Portal (Copenhagen Business School) · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPerspective (graphical)Field (mathematics)Climate changeOrganizational changeOrganizational fieldSociologyPolitical scienceSocial scienceComputer scienceGeologyPublic relationsMathematicsInstitutional theoryArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

We are in crisis mode. Climate change is simultaneously the grandest global challenge and a daily challenge to individuals' perceptions, motivations, and actions. Economic sociology equips us to examine the heart of this crisis: the means, institutions, and regulations of production, exchange, and consumption. To complement this, we must have theoretical and methodological approaches that simultaneously bridge these macro-global and micro-actor levels. The aim of our article is to propose a research agenda for examining climate change from a field perspective to serve as this bridge. Institutional theory defines the "field" as a unit of analysis, rather than focusing on solo organizations or people, to examine all relevant players in processes of stability and change. This concept is influenced by Bourdieu's (1977) notion of "social field" or socially constructed arena: how organizations' interests and activities are mutually constituted through the interactions between them. In this article, we answer three questions regarding the theoretical, methodological, and empirical benefits of taking a field perspective. Why is this helpful for examining climate change? We start with a brief discussion of the relevance of organizations for influencing CO2 production and for contributing to discussions on climate change. We then discuss the relevance of examining relational interactions, between organizations, in stabilizing or changing current positions towards debated actions and towards daily production practices. How is this approach usefully different? We propose that by combining two types of fields - organizational fields and issue fields - we can examine the relationships between organizational actions and discourse. From this we can examine what organizations are doing, how they are "talking," and why they are influenced by this. How does this provide actionable insights? Finally, we demonstrate how both types of fields can be captured simultaneously via big data approaches - by accessing the websites of thousands of organizations and by extracting how they link to each other. Such a research approach helps to inform our understanding of climate change debates and practices, highlights barriers, and offers alternative solutions.

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)0.005
metaresearch head score (Gemma)0.042
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.861
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.007
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1850.051

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 head0.311
GPT teacher head0.488
Teacher spread0.177 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations4
Published2021
Admission routes1
Has abstractyes

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