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Record W3217569887 · doi:10.32920/ryerson.14651817.v1

Corporate social responsibility in the pharmaceutical industry : between trend and necessity

2021· preprint· en· W3217569887 on OpenAlexaff
Cécile Oger

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCorporate social responsibilityPharmaceutical industryBusinessTheme (computing)Social responsibilityMedical prescriptionAccountingPublic relationsPolitical sciencePharmacologyMedicine

Abstract

fetched live from OpenAlex

Despite abundant references in the literature on Corporate Social Responsibility (CRS) and on the specific topic of ethics within the pharmaceutical sector, very little is provided on the general theme of Corporate Social Responsibility and the pharmaceutical industry. The aim of this thesis was therefore to investigate CSR practices and reporting within the global pharmaceutical sector. Secondary research was carried out on the top 65 global pharmaceutical companies. Their CSR activities and reporting were recorded and analyzed. Results indicated that the pharmaceutical industry's CSR practices and reporting follow trends, models and theories observed in other industries and described in the literature. Further to demonstrating that most companies within the industry practice and report on CSR, the research proved that the size of the company, its country of origin, as well as the type of products manufactured (prescription medicine, generics, biopharmaceuticals) all influence the nature of the pharmaceutical company's CSR approach.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.306
Teacher spread0.243 · 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.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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