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Record W2800422650 · doi:10.1002/csr.1509

Analysis of the Canadian national corporate social responsibility strategy: Insights and implications

2018· article· en· W2800422650 on OpenAlexaffabout
Uwafiokun Idemudia, Cynthia Kwakyewah

Bibliographic record

VenueCorporate Social Responsibility and Environmental Management · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsYork University
Fundersnot available
KeywordsCorporate social responsibilityGovernment (linguistics)Political scienceBusinessPublic relationsPublic administrationHuman rightsLaw

Abstract

fetched live from OpenAlex

Abstract Incidences of corporate–community conflict and human rights violation associated with the activities of Canadian extractive companies (CECs) abroad have led to debates at home about the social responsibility of CECs overseas and the role of the Canadian government in corporate social responsibility (CSR). In response to these debates, the Canadian government launched the Canadian national CSR strategy to steer the CSR agenda of CECs. This paper questions and problematizes governmental discourses within the national strategies as a basis for contributing to the debate on the role of government in CSR. We show that the Canadian national CSR strategy embodies the same neoliberal tendencies as the European governmental approach to CSR. However, while the Canadian government's approach to CSR emerged with an emphasis on self‐regulation, it has now morphed into a form of enforced self‐regulation. Hence, the Canadian government adopts both collaborative and confrontation strategies in its efforts to make self‐regulation effective.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.229
Threshold uncertainty score0.894

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.008
Science and technology studies0.0110.007
Scholarly communication0.0100.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.262
Teacher spread0.210 · 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 designQualitative
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

Citations26
Published2018
Admission routes2
Has abstractyes

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