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Record W7036899695

Corporate Social Resposability in the Financial Sector: Are Financial Cooperatives Ready to the Challenge?

2011· other· en· W7036899695 on OpenAlexaboutno aff

Bibliographic record

VenueRedalyc (Universidad Autónoma del Estado de México) · 2011
Typeother
Languageen
FieldComputer Science
TopicMathematics, Computing, and Information Processing
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial institutionCorporate social responsibilityWork (physics)Financial servicesPublicationService (business)Face (sociological concept)InstitutionCorporate governanceFinancial crisis
DOInot available

Abstract

fetched live from OpenAlex

"After the crash of financial institutions and the negative effects of the financial crisis, financial service cooperatives (FSCs) emerged as good performer compared to commercial banks. But this condition will not be enough to face the challenges that the new financial panorama will bring on the banking arena. Among them, challenges related to the corporate social responsibility (CSR) sphere will play a special role. In Canada, the financial regulatory framework forces some federal institutions to publish information on social responsibility. Although FSCs are not forced to disclose information they need to provide CSR information to show their role as an institution capable of innovating in sustainable matters. This work analyses public communications of Canadian FSCs to determine the degree of inclusion of CSR information requested from financial institutions. Results show that the CSR Canadian legal framework has a reduced impact on FSCs communication practices, although with significant differences among them."

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)0.010
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 score0.197
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.006
Scholarly communication0.0050.004
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.043
GPT teacher head0.247
Teacher spread0.205 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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