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Record W2170759360 · doi:10.1177/0149206309335188

The Challenge of Measuring Financial Impacts From Investments in Corporate Social Performance

2009· article· en· W2170759360 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Management · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsSimon Fraser University
FundersIvey Business School, Western UniversityNetwork for Business Sustainability
KeywordsEquity (law)BusinessAccountingMediationAlternative investmentInvestment (military)FinanceProcess (computing)Performance measurementEconomicsMarketingMarket liquidity

Abstract

fetched live from OpenAlex

There is a small, but positive, relationship between corporate social performance and company financial performance. However, research in this area has provided little guidance to managers on how they should measure the financial impacts of their CSP strategies. Commonly used market measures, such as share price, or accounting measures, such as return on equity, are impacted by a host of other variables. These metrics do not provide the necessary level of detail for managers who want to establish an optimal level of CSP investment for their company. Further, academic research has tended to overlook the mediation process between CSP and financial performance. This gap limits the practical application of research and leaves the question of causality unaddressed. The author reviews the research examining the business case for CSP from both the academic and practitioner literatures, and provide recommendations for managers interested in measuring the impacts of CSP investment on financial performance.

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.

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)0.000
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 score0.848
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.055
GPT teacher head0.248
Teacher spread0.193 · 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