Curriculum, deporte y sociedad en América Latina
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The role of the physical environment as a determinant of health is a major concern reported by the general public as well as by many policymakers. However, it remains one of the health determinants for which few available measures or indicators are readily available. This lack of data is compounded by the fact that evidence for direct cause-and-effect relationships in the literature is often equivocal, leading to feelings of uncertainty among the lay public and often leading to indecision among policymakers. In this article we examine one aspect of the physical environment--water pollution in the Great Lakes Areas of Concern (AOCs)--and its potential impacts on a wide range of (plausible) human health outcomes. Essentially, the International Joint Commission, the international agency that oversees Great Lakes water quality and related issues, worked with Health Canada to produce a report for each of the 17 AOCs on the Canadian side of the Great Lakes, outlining a long list of health outcomes and the potential relationships these might have with environmental exposures known or suspected to exist in the Great Lakes basin. These reports are based solely on secondary health data and a thorough review of the environmental epidemiologic literature. The use of these reports by local health policymakers as well as by public health officials in the AOCs was limited, however, by the presentation of vast amounts of data in a series of tables with various outcome measures. The reports were therefore not used widely by the audience for whom they were intended. In this paper we report the results of an undertaking designed to reduce the data and present them in a more policy-friendly manner, using a geographic information system. We do not attempt to answer directly questions related to cause and effect vis-à-vis the relationships between environment and health in the Great Lakes; rather, this work is a hypothesis-generating exercise that will help sharpen the focus of research into this increasingly important area of public health concern.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it