ASPECTOS REFERENTES ÀS INCLINAÇÕES DE CARREIRA E SUAS RELAÇÕES COM O ALINHAMENTO DE VALORES DO EMPREGADO/EMPREGADOR
Bibliographic record
Abstract
The present research aims to study the aspects related to the career preferences and their relationship with the alignment of employees' values, considering the values of their employer. To carry out this study a questionnaire, consisting of 89 questions, was designed using the software Qualtrics. For the survey of the values, the Rokeach Value Survey, which was developed by Rokeach (1973), was used. This survey consists of 36 individual values. As regards the identification of the career anchors of the employees, the instrument developed by Schein (1993), composed of 40 items, called Career Anchors Self-Assessment, was used. The questionnaire was sent by email to the professionals who take part in a discussion group, composed of employees of a public institution of the financial sector, which is based in Rio de Janeiro. Considering the 231 valid questionnaires, through data processing, performed by SPSS software, it was possible to identify the individual values and the most important career anchors for the employees of that public institution. This research also resulted in obtaining information for the development of Human Resources Police. The actions suggested in that Police are intended to increase the alignment of the individual values of the employees, taking into account the values of the referred public institution, in order to increase the satisfaction of the former, which might bring, as a consequence, improves in the performance of the latter.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".