CHILDREN AND THE ENVIRONMENT: VALUING INDIRECT EFFECTS ON A CHILD'S LIFE CHANCES
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
Children can face disproportionately greater risk from environmental hazards because they are kids—smaller bodies, faster metabolisms, shorter attentions spans, less knowledge, and fewer resources. Environmental programs that reduce risks to children produce benefits to society that should be adequately represented so policy makers have more information to help them decide which policies are most worthwhile relative to their costs. The open question is just how exactly to value these reductions in risks to children, risks which can arise either from a direct effect on their health, or an indirect effect on their life chances because of illness in other family members or the degradation of the environment. This article focuses on valuing these indirect effects to a child's life chances. The question addressed here is whether standard benefits estimation adequately captures the indirect effects on healthy children. If policy makers presume caregivers make fully informed, rational choices when dealing with adverse family health, indirect effects are already accounted for in revealed and stated values: estimating indirect effects implies double counting of benefits. But if policy makers fear that caregivers face choice without complete information or experience, indirect effects might be understated. Then it becomes constructive to devote resources to explore the importance of these indirect effects.
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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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