Safeguarding Our Children and the Vulnerable: Integration and a Platform for Prevention
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
ABSTRACT The 2024 Olympic Games may be hailed as the greatest ever. But, though the Games business model may evolve, no new protections emerged for those at play. This paper explores the applicability of an integrative approach to publicly accessible data to increase the security of youth at play from all manner of abuse, including aggression, harassment and bullying. Although open source research (OSR) is a proven business intelligence strategy, it is not yet in our toolbox for safeguarding the vulnerable participants of amateur sports. In this paper, the author demonstrates the potential for an integrative prevention platform, with foundational databases, AI analytics and professional analysis to assure accountability, transparency and adherence to privacy regulations. An integrative platform can serve in better screening of hiring candidates, verifying identity and confirming credentials, monitoring sport management behaviours, educating about risks and threats and managing partnerships, all while supporting preventive action, measuring performance and reporting progress.
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 | 0.002 | 0.001 |
| 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