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Record W6986168362

Operationalizing business ethics in organizations: the views of executives in Australia, Canada and Sweden

2018· article· en· W6986168362 on OpenAlexaboutno aff

Bibliographic record

VenueDeakin Research Online (Deakin University) · 2018
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness ethicsOperationalizationGovernment (linguistics)Information ethicsContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Purpose: Codes of ethics have become the mainstay of the ethics programs of corporations. Many studies have explored their contents, but few have examined what makes them effective. This international study aims to identify the measures viewed as being important by top executives in determining the worth to their organizations of corporate codes of ethics. Design/methodology/approach: Data were collected by questionnaires sent to the top 500 companies ranked by revenue operating in the private sectors in Australia, Canada and Sweden. By analyzing the survey results from the top corporate executives in these countries, the research team was able to test for a number of determinants of effectiveness for codes of ethics. Findings: In a statistically significant model, it was found that four factors related to the internal management of the corporation are positively correlated to executives’ perceptions of the value of their corporate codes of ethics. Research limitations/implications: Future research may seek to address features of this study that limit its generalizability, as it was conducted on the largest of companies in each country and thus this sample may not reflect the way that business ethics are managed in smaller organizations in those countries. Originality/value: If executives see particular items as important to their business ethics success, one could postulate that this has arisen from a perception that implementing these measures has been effective for their organizations. This provides guidance to other organizations on what items could enhance the effectiveness of their codes of ethics.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
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 head0.193
GPT teacher head0.459
Teacher spread0.266 · 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 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
Published2018
Admission routes1
Has abstractno

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