Desempeño laboral y climaterio en trabajadoras de instituciones públicas
Bibliographic record
Abstract
BACKGROUND: During climacteric, the presence of disabling symptoms and the higher incidence of chronic diseases, may impair the job performance of women. AIM: To relate job performance levels with the climacteric period and associated factors in working women aged from 42 to 55 years old. SUBJECTS AND METHODS: In a cross-sectional and correlative design, 64 secretaries at two public organizations at the Eighth Region of Chile, were assessed using the following instruments: Menopause-Specific Quality of Life Questionnaire (University of Toronto), adapted for Chile by PROSAM, Climacteric Self-care Questionnaire, Perceived Social Support Scale and Biodemographics Variables Questionnaire. A Perception of the Job Performance Scale was applied to the persons that superintended these woman. RESULTS: The Department Heads or persons supervising these women, determined that most workers did their work well. The best evaluations were given by older bosses. Most women under study showed a moderate alteration of the Menopause Quality of Life. A deficit of self-care during the climacteric period was detected in 92.2%. The perceived social support from friends correlated with job performance. Menopause quality of life in its different domains had no correlation with job performance variable. CONCLUSIONS: No association between changes during the climacteric period and job performance was observed among women participating in this study.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".