MétaCan
Menu
Back to cohort
Record W4399975138 · doi:10.1111/basr.12358

“Creating shared value”: Time for a normative extension?

2024· article· en· W4399975138 on OpenAlexaff
Mark S. Schwartz

Bibliographic record

VenueBusiness and Society Review · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsYork University
Fundersnot available
KeywordsExtension (predicate logic)NormativeValue (mathematics)PsychologySocial psychologySociologyComputer sciencePolitical scienceMathematicsStatisticsLawProgramming language

Abstract

fetched live from OpenAlex

Abstract Porter and Kramer's “creating shared value” (CSV) proposal has achieved significant penetration into both the academic and corporate communities. Building on other critiques of CSV, this paper assesses whether the CSV framework, notwithstanding its popularity, currently possesses an appropriate and adequate theoretical foundation to represent an overarching normative framework for the entire business and society field. The analysis does so by comparing CSV with a series of other dominant business and society approaches including corporate social responsibility, business ethics, stakeholder management, sustainability, and corporate citizenship. The analysis finds that while CSV does address the fundamental business and society normative requirement that business activities should contribute to sustainable net societal value , it currently fails to adequately incorporate the equally important notions of (i) appropriately balancing stakeholder interests with those of the corporation's shareholders, as well as (ii) demonstrating sufficient accountability (i.e., taking responsibility) by properly reporting on and addressing any negative impacts resulting from the firm's activities. The paper concludes with a revised and expanded restatement of the CSV concept, which attempts to take into account and address its current theoretical limitations in order to enhance its appeal as an overarching business and society normative paradigm.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.691
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.291
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBusiness and Society ReviewSame topicCorporate Social Responsibility ReportingFrench-language works237,207