Perception of Social-Sexual Behavior and Workers’ Productivity in Selected Banks in Nigeria
Bibliographic record
Abstract
In this study, the effect of social sexual behavior on workers’ productivity is examined from the perspective of individual managers, individual employees and work groups. A case study of banks in Delta State, Nigeria, is adopted to investigate the effect of social sexual behavior on workers’ productivity from a different cultural perspective as obtainable in literature. A measure of workers’ productivity and their interaction with components of social sexual behavior; sexual harassment and workplace romances, was obtained from 110 employees sampled from three banks within the study region through a questionnaire. Sex, age, marital status, education and employment status were adopted as moderating variables for the study. Multiple regression analysis was used in testing the hypotheses of the study. Result of this work reveal amongst others that sexually suggestive jokes or comments about a person’s dress or body, made in their presence or directed towards them from a co-worker or customer could lead to demoralization of workers and poor interpersonal job performance between coworkers or of a worker towards a customer. The study further reveal that workplace romance could trigger jealousy among other employees, thereby leading to a failed interpersonal job performance and low productivity. The study recommends that organizations should clearly define their climate for social sexual behavior to both workers and customers through policies and sensitization with strict penalties given to defaulters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".