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Record W3004993668 · doi:10.1007/s10389-020-01219-w

Corporate social responsibility vs. financial interests: the case of responsible gambling programs

2020· article· en· W3004993668 on OpenAlexaff
Ingo Fiedler, Sylvia Kairouz, Jennifer Reynolds

Bibliographic record

VenueJournal of Public Health · 2020
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsConcordia University
Fundersnot available
KeywordsCorporate social responsibilityIncentiveGermanSocial responsibilityPublic relationsBusinessAccountingFinanceEconomicsPolitical scienceMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Aim Corporate social responsibility (CSR) is supposed to play an important part in public health. Critics argue that opposing financial interests can prevent companies from implementing effective CSR programs. We shed light on this discussion by analyzing CSR programs of gambling operators. Subjects and methods Two data sets are used: (1) seven responsible gambling (RG) programs of German slot machine hall operators and (2) a survey carried out among 512 problem gamblers in treatment who play primarily in slot machines halls. Results Results show that the RG programs list mostly mandatory measures with one major exception: to approach possible problem gamblers with the intention to help them. However, operators’ staff approach only 1% of problem gamblers. Conclusion We argue that the observed ineffective implementation of voluntary CSR measures is grounded in the strong financial incentive of operators to serve precisely the group they should stop from playing: problem gamblers. We conclude that financial interests reduce the effectiveness of CSR.

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)0.008
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.463
GPT teacher head0.486
Teacher spread0.024 · 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 designOther design
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

Citations21
Published2020
Admission routes1
Has abstractyes

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