Ensaios sobre atitudes em relação a iniciativas de paridade de género e comportamentos de cidadania organizacional
Bibliographic record
Abstract
Gender equality and empowerment of all women and girls, beyond a UN’s sustainable development goal (SDG 5), has become a fight for all generations (actual and futures), facing a controversial debate among authors, leaders, and organizations. Moreover, ways to achieve gender diversity within organizations, without compromising individual and organizational performance challenges managers and policy makers worldwide. Nevertheless, to the best of our knowledge, studies connecting corporate social responsibility (CSR), employee’s attitudes, organizational citizenship behavior (OCB), and job satisfaction (JS) are limited. Particularly analyzing employees’ attitudes and behaviors in different contexts—developing vs. developed countries, for instance. The novelty of this thesis lays in the scrutiny of such phenomena, investigating what influences employee’s attitudes towards gender parity initiatives and OCBs in three countries—Brazil, Canada, and Portugal. A sample of 2.425 observations was analyzed to investigate the antecedents of attitudes towards gender equity initiatives (AGPI) and its effect on Job Satisfaction (JS), also testing the influence of job satisfaction, organizational commitment, and CSR perceptions on OCBs. Our unit of analysis was the individual; hence, a convenience sample of public and private Higher Education Institutions (HEIs) employees had been used. The option to work with HEIs professors and researchers considered that such professionals represent the engine of social development and influence of future generations, either within their institutions or their area of expertise. A dual approach was adopted: (1) investigate the influence factors on attitudes towards gender parity initiatives, and (2) test different predictors of organizational citizenship behaviors. Findings indicated that despite in opposed directions, both social dominance orientation (SDO) and status threat (ST) influenced employees’ AGPI, being the former the most determinant within the three countries studied. Portuguese and Brazilian employees are less supportive of gender parity initiatives, when compared to Canadian. AGPI influence over job satisfaction, unfortunately, remains unexplained. Additionally, employees’ perceptions of CSR initiatives exerted a positive and statistically significant influenced on JS, while positively affecting organizational commitment (OC). Finally, CSR perceptions and OC were found to exert a positive influence on OCBs, being the preponderant variable among HEI employees from the three studied countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".