MétaCan
Menu
Back to cohort
Record W2219675805

Corporate Social Responsibility as Obligation: Lessons from India

2015· article· en· W2219675805 on OpenAlexaff
Supriya Routh

Bibliographic record

VenueSSRN Electronic Journal · 2015
Typearticle
Languageen
FieldNeuroscience
TopicFree Will and Agency
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCorporate social responsibilitySocial responsibilityConstitutionObligationCorporationLaw and economicsState responsibilityPolitical scienceLawInterpretation (philosophy)BusinessSociologyHuman rights
DOInot available

Abstract

fetched live from OpenAlex

Even Milton Friedman, who assigned corporations only with the responsibility of increasing profits, had acknowledged that corporations are to conform to the “basic rules of the society” for their very existence. According to Friedman, the idea of social responsibility could only be voluntary. Such as view, however, ignores the entrenched nature of corporations in the social fabric. If corporations ought to pursue an irresponsible and unidirectional profit motive in negation to all other social and environmental considerations, there are moral reasons why a society would not want corporations to be constituents of the society. In the backdrop of the legally mandated corporate social responsibility (CSR) contribution in India, in this essay I argue that no real idea of responsibility can be discretionary in the sense that it depends on the whims and fancies of a corporation. If responsibility is to be real, it must be compulsory. The Constitution of India envisages such responsibility for the various social actors including the citizens and the state (and corporations, by judicial interpretation). Such an idea of obligatory responsibility, which permeates the Indian constitution, is akin to what Iris Young calls social connection responsibility that is diffused in the society rather than emanating from liability for fault.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.310
Teacher spread0.228 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicFree Will and AgencyFrench-language works237,207