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Record W4391746291 · doi:10.3390/jrfm17020068

Insights into Sustainability Reporting: Trends, Aspects, and Theoretical Perspectives from a Qualitative Lens

2024· article· en· W4391746291 on OpenAlexvenueno aff
Banu Dinçer, Caner Dinçer

Bibliographic record

VenueJournal of risk and financial management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
FundersGalatasaray Üniversitesi
KeywordsSustainabilityQualitative researchLegitimacyRealmEngineering ethicsScope (computer science)Thematic analysisStakeholderConceptual frameworkManagement scienceIdentification (biology)SociologyPublic relationsPolitical scienceSocial scienceComputer scienceEngineeringEcology

Abstract

fetched live from OpenAlex

This review aims to provide a comprehensive synthesis of the coverage of sustainability reporting (SR) aspects within the corpus of qualitative SR literature. It seeks to elucidate the theoretical and conceptual foundations that have guided the trajectory of the sustainability field and illuminate the qualitative methodologies used in this body of literature. Employing a systematic review methodology, this study undertakes an exhaustive examination of 242 selected empirical studies on sustainability reporting conducted during the period spanning from 2001 to 2022. The noteworthy contribution of this review to the realm of sustainability research lies in its identification of unexplored and underexplored domains that merit attention in forthcoming investigations. These include but are not limited to employee health and safety practices, product responsibility, and gender dynamics. While stakeholder theory and institutional theory have been dominant theories within the selected literature, the exploration of moral legitimacy remains largely underinvestigated. It is essential to underscore that this review exclusively encompasses qualitative studies, owing to the richness and versatility inherent in qualitative research methods. This deliberate selection enables researchers to employ diverse methodological and theoretical frameworks to gain a profound understanding of engagement within the practice of sustainability reporting. This review introduces an interesting approach by considering the thematic scope, as well as theoretical and methodological choices, observed across the selected studies.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.294
Teacher spread0.278 · 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 designTheoretical or conceptual
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

Citations9
Published2024
Admission routes1
Has abstractyes

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