The Socio-Critical Perspective of Mathematical Modeling: A Proposal on Prostate Cancer
Bibliographic record
Abstract
In this study, we approach Mathematical Modeling from a socio-critical perspective. Our aim was to achieve reflection and criticality in discussions about prostate cancer in the context of the Blue November campaign, which started in November 2011, hapenning every year from then and is dedicated to raising awareness about prostate cancer. Since Brazillian culture is still imbued with sexual prejudices, we think it is important to have, in our schools, talks about the taboo related to prostate cancer and the diagnostic tests to check a man prostate condition, especially in the case of the rectal examination. To this end, we conducted a qualitative, empirical study with 30 eighth-grade elementary school students in a school located in the city of Salinópolis, state of Pará, northern region of Brazil. As results, we highlight interdisciplinary, social, health and education debates that addressed behavioral issues, awareness, information and statistical literacy through reading, discussion and analysis of the mathematical models involved in the unfolding of the proposal.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".