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Internal Adaptation or Institutional Legitimacy? The Evolution of CSR Reporting

2017· article· en· W2765977958 on OpenAlexaboutno aff
Xiaoyu Liu, Scott Rankin, Loren Falkenberg

Bibliographic record

VenueAcademy of Management Proceedings · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsLegitimacyCorporate social responsibilityBusinessAdaptation (eye)Investment (military)AccountingEnvironmental reportingResource (disambiguation)Institutional theoryTurnoverIndustrial organizationPublic relationsEconomicsPolitical scienceManagementPsychology

Abstract

fetched live from OpenAlex

Despite the proliferation of voluntary environmental, social and economic disclosure by firms over the past 25 years, there are few accounts of how the actual practice of CSR reporting evolves within firms that choose to adopt it. This comparative case study in the Canadian energy industry addresses this gap. It finds that neither external legitimacy forces nor internal resource dependence explanations are sufficient to understand the motivations for reporting or the changes over time. Instead, it finds a common pattern of iterative interaction between external and internal influences. Specifically, it finds that while the impetus for reporting initially is largely external, the investment in resources required to report generates internal commitment to the principles of CSR over time.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0030.017
Scholarly communication0.0110.006
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.078
GPT teacher head0.314
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2017
Admission routes1
Has abstractyes

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