Advances in the Global Initiative for Childhood Cancer: implementation in Latin America and the Caribbean
Bibliographic record
Abstract
This report describes the status of childhood cancer control initiatives in Latin America and the Caribbean (LAC). Progress between 2017 and 2023 is measured using the outcome indicators from the Pan American Health Organization (PAHO) childhood cancer logic model aligned with the World Health Organization Global Initiative for Childhood Cancer (GICC). This report also describes the advances, barriers, and facilitators for the implementation of the GICC at the Regional level. Methods used in this report encompassed a comprehensive approach, incorporating a literature review, interviews, surveys, and a Delphi study developed by the technical team of the PAHO Non-Communicable Diseases and Mental Health Department and by the GICC LAC working group. Since 2017, there has been a substantial increase in the number of countries that have included childhood cancer in their national regulations. Currently, 21 LAC countries are involved in the GICC implementation, activities, and dialogues. However, the objectives for 2030 will only be achieved if Member States overcome the barriers to accelerating the pace of initiative implementation. There is an urgent need to increase the efforts in childhood cancer control in LAC, especially regarding the prioritization of timely detection, essential diagnostics, access to cancer treatment, palliative care, and close follow-up of children and adolescents with cancer.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".