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Record W4396718494 · doi:10.61838/kman.isslp.3.1.5

Employee Experiences with Workplace Discrimination Law

2024· article· en· W4396718494 on OpenAlexaff
Seun Adu Bakare, Nilofar Nouhi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Law and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsLabour lawPsychologyLawPolitical scienceSociologySocial psychology

Abstract

fetched live from OpenAlex

Workplace discrimination remains a pervasive issue with significant impacts on employee well-being and organizational effectiveness. This study aims to explore the nuances of employee experiences with workplace discrimination law, focusing on how individuals perceive, react to, and are affected by discriminatory practices in their workplaces. A qualitative research design was employed, using semi-structured interviews to collect data from 30 participants who had experienced or observed workplace discrimination. The study targeted theoretical saturation to ensure comprehensive coverage of relevant experiences. Data were analyzed using NVivo software, which facilitated thematic analysis and helped identify key themes and categories within the interview transcripts. Three main themes emerged from the data: Perceptions of Discrimination, Experiences with Legal Processes, and Impact on Workplace Culture. Each theme included multiple categories, such as Legal Knowledge, Personal Impact, Reporting Procedures, Outcomes of Legal Action, Changes in Workplace Dynamics, and Long-term Effects. These categories encompassed various concepts like understanding of rights, emotional distress, confidentiality issues, settlement outcomes, changes in team cohesion, and shifts in organizational policies. The findings reveal the complexity of workplace discrimination and underscore the need for robust organizational policies and practices that can effectively prevent and address discrimination. The study highlights the importance of enhancing legal and procedural knowledge among employees, improving reporting and support systems, and fostering an inclusive culture to mitigate the adverse effects of discrimination on workplace dynamics and employee health.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.248
Teacher spread0.223 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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