A atuação do IFES no interior do Espírito Santo : uma análise comparativa com base no ENEM
Bibliographic record
Abstract
This study aims to point out the importance of the expansion of the Rede Federal to the interior of the state of Espirito Santo, in terms of educational development of students from cities away from Greater Vitoria, based on an analysis of the performance of four Campuses of the Federal Institute of Espirito Santo - Aracruz, Cachoeiro de Itapemirim, Nova Venecia and Piuma - in the Brazilian National High School Examination (ENEM), in the years 2014 and 2015. The ENEM was the metric adopted for analysis because other comparative analysis tools such as the Human Development Index (HDI) and the Economic Well-Being Index (IEWB), which could be used to support an analysis of this nature, do not have annual updates in Brazil, the first being based on the Census developed by Brazilian Institute of Geography and Statistics (IBGE) and the second a tool developed in Canada and that, although its application was defended as a substitute for the use of GDP (Gross Domestic Product) as a measure of Wealth of a country, does not have wide acceptance like the last. The aim of this study was to verify how the IFES Campi perform in the ENEM in comparison with the other educational institutions of their respective municipalities, besides comparing the performance of the Campi with the public schools of their municipality and between themselves. The proposed methodology is an exploratory study, with a qualitative and quantitative approach of a descriptive nature. The data collected from primary source will be through interviews with managers of the Campi researched, and the secondary data from documental and bibliographic research. The results obtained from secondary sources showed that there was a decrease in the performance of all Campi in the year 2015, when there was also budgetary contingency in the units, which indicates a correlation between performance and investments made. The analysis of the data aims on the Gibbs approach, which proposes the categorization of the data from a comparative analysis, in which the content of the interviews generates tables of information to demonstrate the vision of the speakers about the Federal Institute of Education
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".