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The Social Responsibility of Managers: Reassessing and Integrating Diverse Perspectives

2011· article· en· W1960057152 on OpenAlexaff
Steven Globerman

Bibliographic record

VenueBusiness and Society Review · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsProfit maximizationOpportunismSocial responsibilityPublic relationsProfit (economics)MaximizationCorporate social responsibilityBusiness ethicsBusinessEconomicsSociologyPolitical scienceMicroeconomicsMarket economy

Abstract

fetched live from OpenAlex

The social responsibility of business has been a prominent issue in the academic and practitioner literatures, as well as in the curricula of business schools, for many years. While Friedman's iconic defense of profit maximization as the responsibility of management has been widely and extensively assailed, emerging positions on the role of business in society offer little clear and practical guidance to current managers, as well as Masters of Business Administration students. I argue in this article that the focus of the debate should shift to considering how the rules of the game surrounding business' behavior should be formulated and what the role of socially responsible managers should be in helping to establish those rules. My contention is that the goal of society should be to strengthen the linkage between the achievement of social objectives and profit maximization by business through “bright line” regulations and laws. Socially responsible managers will participate in setting the rules of the game by advising policymakers on how specific regulations and laws can be structured so that they most effectively condition the linkage between social objectives and profit maximization. If there is a unique social responsibility of managers beyond profit maximization, it is to participate in the policymaking process “honestly,” that is, without attempting to game the system through guile and opportunism.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.791
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.059
GPT teacher head0.298
Teacher spread0.239 · 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 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

Citations5
Published2011
Admission routes1
Has abstractyes

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