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Record W2604544712 · doi:10.5430/afr.v6n2p121

Implementing Integrated Reporting: Case Studies from the Italian Listed Companies

2017· article· en· W2604544712 on OpenAlexvenueno aff
Renato Salvatore Camodeca, Alex Almici

Bibliographic record

VenueAccounting and Finance Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsIntegrated reportingProcess (computing)BusinessSustainability reportingTransition (genetics)SustainabilityAccountingKnowledge managementProcess managementMarketingPublic relationsComputer scienceCorporate social responsibilityPolitical science

Abstract

fetched live from OpenAlex

The purpose of this paper is to explore the change experienced by the Italian listed companies through the implementation of integrating reporting. The objective of this study is to shed light on the company’s moving reasons towards integrating reporting and on its effects on the company’s thinking approach.This paper builds on multi-source data gathered through web-site visits, company materials and interviews, according to an interpretive case study approach.The authors found that the process of change experienced by the selected companies deserves consideration for at least two reasons: on the one hand, as a transition from a stand alone to an integrated thinking approach; on the other hand, as a transition from an implicit to a more explicit approach to sustainability.The paper is, to the best of the knowledge, the first one to explore the process of change experienced by the Italian listed companies through the implementation of integrated reporting.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
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 head0.242
GPT teacher head0.436
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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

Citations17
Published2017
Admission routes1
Has abstractyes

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