Servidores com deficiência de instituições públicas de ensino superior e a pandemia da Covid-19
Bibliographic record
Abstract
For a long time, people with disabilities were excluded from social life and prevented from performing different occupations. In the course of history, they were segregated, integrated and were only included after the emergence of different social movements related to human rights. Although inclusion policies have been proposed, legislation is still needed to ensure all the real guarantees of opportunities for inclusion in different contexts. Therefore, there are still difficulties to be overcome for the inclusion of everyone. In relation to the labor market, people with disabilities may face difficulties in the process of admission, adaptation and permanence in employment.The same is observed with regard to architectural and urban accessibility, transportation, communication and information.The aim of this study was to describe the process of admission and monitoring of employees with disabilities in public institutions of higher education.Specifically, we sought to identify the demands and problems related to the activities carried out by these servers, and describe the accessibility and types of barriers that exist in a typical workday in the face-to-face and remote period established in the Covid-19 pandemic.In Minas Gerais there are eleven public universities. All of them were contacted and five became partners in this study.The federal public employee of these institutions were sent an electronic invitation containing the formalization for participation and the period for the videoconference. It was used for the online interviews a script with open questions, the Brazil Economic Classification Criteria and the Canadian Occupational Performance Measure. The interviews were recorded, transcribed and submitted to thematic categorical content analysis.The results show a reduced number of employees with disabilities in the institutions, reveal attitudinal, architectural and communication/information barriers, as well as the accessibility of co-workers, and show flaws in the admission and monitoring process of most employees with disabilities in the institutions. The set of information on the subject can help universities improve the process of welcoming and adapting servers with disabilities, as well as assisting in the development of strategies for the inclusion of everyone in the university environment.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".