Bibliographic record
Abstract
In North Carolina, a faith-based 501(c)(3) nonprofit organization facilitates a child sponsorship program that connects North American evangelical Christians with at-risk children in one of postwar Guatemala City's most violent neighborhoods: La Paloma. Pitched in the name of gang prevention, child sponsors help create a context in which these Guatemalan kids might choose God over gangs. Based on fieldwork in North Carolina and in Guatemala, with both sponsors and the sponsored, this article explores how child sponsorship makes the work of gang prevention dependent on the work of self-cultivation. It is an ethnographic approach attuned to what this article understands as the subject of prevention, that is, the individual imagined and acted upon by the imperative to prevent. This includes at-risk youths, in all their racialized otherness, but also (and increasingly so) North American evangelicals who self-consciously craft their subjectivities through their participation in gang prevention. The subject of prevention's observable outcome is a kind of segregation with its own spatial logic. The practice of evangelical gang prevention ultimately produces an observable kind of inequality that says something about the surgically selective nature of Central American security today. Some Guatemalan youth connect with North Americans. Others get left behind.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.068 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".