Review of Education‐Focused Health Impact Assessments Conducted in the United States
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
BACKGROUND: Health impact assessment (HIA) provides a structured process for examining the potential health impacts of proposed policies, plans, programs, and projects. This study systematically reviewed HIAs conducted in the United States on prekindergarten, primary, and secondary education-focused decisions. METHODS: Relevant HIA reports were identified from web sources in late 2015. Key data elements were abstracted from each report. Four case studies were selected to highlight diversity of topics, methods, and impacts of the assessment process. RESULTS: Twenty HIAs completed in 2003-2015 from 8 states on issues related to prekindergarten through secondary education were identified. The types of decisions examined included school structure and funding, transportation to and from school, physical modifications to school facilities, in-school physical activity and nutrition, and school discipline and climate. Assessments employed a range of methods to characterize the nature, magnitude, and severity of potential health impacts. Assessments fostered stakeholder engagement and provided health-promoting recommendations, some of which were subsequently incorporated into school policies. CONCLUSIONS: Health impact assessment is a promising tool that education, health, and other stakeholders can use to maximize the health and well-being of students, families, and communities.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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