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Record W2037594476 · doi:10.5539/jsd.v4n2p16

A Delphi Study to Identify Corporate Social Responsibility Indicators: The Case of Greek Telecommunication Sector

2011· article· en· W2037594476 on OpenAlexvenueno aff
Grigoris Giannarakis, Nikolaos Litinas, Ioannis Theotokas

Bibliographic record

VenueJournal of Sustainable Development · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate social responsibilityDelphi methodBusinessOrder (exchange)Corporate governanceDelphiIndex (typography)Performance indicatorAccountingTelecommunicationsMarketingIndustrial organizationComputer sciencePublic relationsFinance

Abstract

fetched live from OpenAlex

The Telecommunication sector deals with numerous social and operational challenges such as technological development, increased demand for telecommunication services, health concerns and environment protection. The aim of this paper is to identify both general and sector-specific indicators in order to measure the Corporate Social Responsibility (CSR) performance. The Telecommunication sector has analyzed and identified the main stakeholders that affect and are affected by business operations. Six main stakeholders, namely suppliers, customers, corporate governance, environment, society and human resources and forty three indicators are indentified concentrating on the Greek market with the use of Delphi technique. Additionally, the study presents a specific formula for each indicator so as to measure CSR performance in specific terms. The contribution of the study is to formulate an aggregate CSR index and translate CSR concerns into specific indicators and to recommend a methodology in order to propose indicators applicable to any sector.

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)0.019
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.177
GPT teacher head0.437
Teacher spread0.260 · 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 designQualitative
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

Citations15
Published2011
Admission routes1
Has abstractyes

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