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Organizational Politics: Scarcity of Resources, Employee’s Personality & Employee’s Diversity

2023· article· en· W4385558790 on OpenAlexfundno aff
Unyime Okon Etim, Christabel Divine Brownson, Ubong Augustine Akpaetor

Bibliographic record

VenueGlobal Journal of Human Resource Management · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsnot available
FundersDivision of Human Resource DevelopmentBrock University
KeywordsCommissionScarcityGovernment (linguistics)Diversity (politics)BusinessPoliticsLocal governmentService (business)Public relationsPublic administrationMarketingPolitical scienceFinanceEconomicsLaw

Abstract

fetched live from OpenAlex

Employees of different backgrounds are employed to help achieve corporate objectives. The complexities that exist among these employees are expected to be effectively managed through proper organizational political practices. As such, this study examines the relationship between organizational politics and employee’s diversity in Akwa Ibom State Local Government Service Commission. Using a survey research design, 118 employees of the commission were examined and the findings revealed that scarcity of resources has positive and significant relationship with employees’ diversity in Akwa Ibom State Local Government Service Commission (r = 0.614, p<0.000); and employee’s Personality has positive and significant relationship with employees’ diversity in Akwa Ibom State Local Government Service Commission (r = 0.662, p<0.000). It was concluded that organizational politics has positive and significant relationship with employees’ diversity in Akwa Ibom State Local Government Service Commission. It was recommended that top level managers in the commission should encourage fair and equitable practices in the organization as this would help to lessen high political practices among the employees.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.003
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 head0.044
GPT teacher head0.275
Teacher spread0.231 · 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.

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
Published2023
Admission routes1
Has abstractyes

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