Programa de Coleta Seletiva da UFPA e seu impacto na promoção de emprego e renda dos catadores de materiais recicláveis selecionados para o período 2022/2024
Bibliographic record
Abstract
The objective of this paper was to discuss the impact of the recycling program at the Federal University of Par (UFPA) on the income of recyclable waste collectors.For this, it used quantitative and qualitative data as a methodology, collected through interviews and data collection with the collectors of recyclable materials from Sons of the Sun Cooperative , as well as interviews and analysis of secondary data on the other two cooperatives approached (COOTARAL and COOTPA), with employees of the UFPA recycling program, from 02/01/2023 to 02/18/2023.In addition to secondary data produced by the UFPA City Hall.The basic theory was the precepts defended by the authors of the Circular Economy, where the secondary raw material (recyclable waste) is reinserted in the production and the collectors are benefited with the creation of jobs and income and its introduction in this productive chain.In this sense, we start from the hypothesis that the use of recyclable materials contributes to economic and socio-environmental sustainability.As a result, according to the selective collection data, there was no increase in the income of collectors from cooperatives and associations that collected recyclable material at UFPA, but the weekly income was significantly more stable during the period in which they were receiving the material.from the university.In addition, workers from all cooperatives expressed strong approval for the program, citing factors such as the commitment of university staff, the quality of the material collected, and the work environment as some of the highlights of the program.When comparing the results with data from the ACCSB cooperative in 2018, we observe that the income of the CCMRFS cooperative during the collection period at UFPA in 2022 represents an increase of approximately 25% compared to the income of the ACCSB in 2018.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".