The Intersection of Law and Sanitation for Sustainable Communities: Exploring practices beyond borders
Bibliographic record
Abstract
This article presents an exploratory overview of sanitation practices across Brazil and in Ontario, Canada, with a focus on laying the groundwork for a nuanced understanding of the subject. Employing a qualitative research approach and systematic document review, the study examines peer-reviewed research articles, governmental reports, policy documents, and official statistics from the regions under scrutiny. While not exhaustive, this research offers valuable insights into sanitation challenges and efforts, serving as a foundational resource for future legal research and policymaking. Tracing the historical evolution of sanitation practices and their alignment with sustainability principles and Sustainable Development Goals (SDGs) 6 and 11, the study underscores the importance of sanitation in promoting public health, enhancing quality of life, and safeguarding access to essential services. It also briefly touches upon the shift towards private sector involvement in sanitation services and the challenges it poses, highlighting the significance of user participation in decision-making processes and addressing financing challenges within the sanitation sector. Emphasizing a global perspective on sustainable sanitation practices, this research sets the stage for deeper legal examinations and policy endeavors in the field.
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.
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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.051 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| 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".