Streetcorner Environmental Injustice:
Bibliographic record
Abstract
Every weekday morning in Quito, Ecuador some poor Amerindian mothers take their small children to intersections in the streets where the children spend the day begging from passing motorists. The parents take their children to intersections with stop lights in streets with medians and station the children in the median (see diagram). When cars stop at the lights, the children run up to the front doors of the cars (it is convenient because the driver's side is closest to the median) with their hands outstretched, palms up. The most common scene involves a small child, aged three to six, looking up at a driver behind the rolled up window of a sport utility vehicle. When the light changes, the cars, light trucks, and trucks accelerate, emitting a cloud of exhaust, and the children run back to the median. Unfortunately, gasoline in Ecuador is still leaded, so the particular way in which begging occurs in this increasingly motorized society maximizes the children's exposure to lead from the vehicles ' exhaust. Studies show elevated levels of lead in the blood of street children.
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 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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.118 | 0.003 |
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; both teacher heads agree on what is shown here.
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".