MétaCan
Menu
Back to cohort
Record W4415490190 · doi:10.54647/management630174

WHAT WORKPLACE PROTECTIONS DO EMPLOYEES HAVE IN US ORGANIZATIONS? A MODERN-DAY ANALYSIS OF DISTRIBUTIVE AND PROCEDURAL JUSTICE SYSTEMS AS A METHOD OF EMPLOYEE EQUITY AND POWER

2019· article· en· W4415490190 on OpenAlexaff
Steven V. Cates, Jason Baird Jackson, Carrie O’Hare, Nanda Nandakumar Purohit, Enrique Navarro Asencio, Seán Doyle

Bibliographic record

VenueSCIREA Journal of Management · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsCanadian Women's Health Network
Fundersnot available
KeywordsDistributive justiceProcedural justiceEquity (law)Distributive propertySample (material)Economic JusticeWork (physics)Field (mathematics)

Abstract

fetched live from OpenAlex

The concepts of Procedural and Distributive Justice have been subject to extensive research since it was theorized in the 1970’s in the fields of social and industrial/organizational psychology. The weakness with the majority of the research is the lack of actual employees as the sample populations and used mostly students. Anderson and Ruderman (1987) were some of the original scholars who used actual federal employees in their studies and this research was considered one of the major research studies in the field of Procedural and Distributive Justice. This research has undertaken the concepts of the original study that was conducted by Anderson and Ruderman and created a comparison study that used a similar research design framework. A sample of 521 employees from multiple industries across all geographic locations in the U.S. were obtained. Using the Survey from the Anderson and Ruderman studyallowed for the same questions to be asked today versus 1987 of employees about Justice Systems in their jobs and employment situations. Similar Hypotheses were tested. Results were found to be similar in most cases with some slight deviations. The variances can be potentially attributed to the use of more advanced statistical tools that are available in today’s research than was available and economically feasible for use in 1987. The findings indicate a need for management to provide equal treatment of employees and provide them with greater opportunities for engagement and involvement in their work environment.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.295
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 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueSCIREA Journal of ManagementSame topicRegulation and Compliance StudiesFrench-language works237,207