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Dimensions in EDI Policy Development

2022· book-chapter· en· W4281395874 on OpenAlexaff
Brian Roland Gay

Bibliographic record

VenueAdvances in human resources management and organizational development book series · 2022
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsRealmMulticulturalismMultidisciplinary approachSociologyPerformative utteranceDiversity (politics)Function (biology)IntersectionalityEngineering ethicsEpistemologyPolitical scienceSocial scienceEngineeringPedagogyGender studies

Abstract

fetched live from OpenAlex

This chapter reviews literature for a discussion on future influences on workplace diversity management. With an emphasis on the role culture plays on the moral philosophy of individuals, it is taking the viewpoint that there is a distinction between workplace and business ethics. By placing the individual within the realm of non-traditional and traditional, the chapter intends to add to the discourse of future influences on EDI policy development and subsequent understanding. The term language is viewed not only from its linguistic function. It is also presented from its ability to influence power dynamics. When speaking of language, due to the geographical regions of the research papers and the dominant research areas, the performative language is English. This chapter applies a multidisciplinary lens as it presents the following dimensions as key determinants in the emerging workplace ethical field: diversity's constant state of discovery and redefinition, multiculturalism, interculturalism, and intersectionality.

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)0.011
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.006
Science and technology studies0.0070.015
Scholarly communication0.0200.015
Open science0.0020.009
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0080.001

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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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