Ethical considerations for Forensic Genetic Frequency databases: First Report conception and development
Bibliographic record
Abstract
The Forensic Databases Advisory Board (FDAB), an independent board that assists the International Society for Forensic Genetics (ISFG), has presented a First Report on ethical aspects of the following Forensic Genetic Frequency Databases (FGFD): EMPOP, STRidER and YHRD. The FDAB designed an ethical framework to evaluate the content of these FGFD, and the factors to be considered for retention and acceptance of submissions. The FDAB framework proposes to categorize submissions according to the risk of having contravened the universal ethical principles outlined by international organizations, and the guidelines adopted by the ISFG. The report has been open to discussion by the scientific community since 2023. Herein we present the conception and development of the First Report along with a summary of its content, with consideration of the feedback received.
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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 | 0.183 | 0.329 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".