Randomised impact evaluation of a CBT-based intervention to foster socioemotional skills in vulnerable youth in Brazil
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
In this experiment, we evaluate an evidence-backed, low-cost intervention to improve academic performance and reduce risk-behaviour through the development of socioemo- tional skills amongst vulnerable children – those who are most at-risk of being victims and/or perpetrators of violence. We will conduct a Cluster-randomised Trial (CRT) at school level in two municipalities in Brazil to evaluate the SEJA intervention that is based on successful experiences conducted in Chicago, Liberia and Canada. SEJA has low direct costs and is scalable when compared to similar interventions. The program has been designed to leverage municipalities’ existing personnel and infrastructure, making it ideal for implementation in low and medium income countries. We will estimate the interventions’ causal impacts on short and long-term outcomes. On the short-term, we look at outcomes such as socioemotional skills, academic performance, school frequency and enrolment in high school. The longitudinal design of our study allows us to conduct follow-up rounds of survey and administrative data collection to estimate causal impacts on long-term outcomes, such as criminal sanctions, victimisation, other self-reported vul- nerabilities, participation in anti-poverty programs and labour market outcomes.
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 | 0.027 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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