Forensic epistemology: A need for research and pedagogy
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
This is the third in a series of articles reporting on forensic epistemology. Our first two research articles presented scientific results that are based in experimental design; including quantitative and qualitative responses from forensic science practitioners to scenarios and evidence. Based on a synthesis of this research there is evidence of a knowledge gap in formal reasoning for some forensic practitioners, and a limited understanding of case-specific research. Combining these results with a review of the current literature in the field of forensic reasoning, we now offer evidence of teaching and research strategies that can help increase the epistemic status (Confidence in, and justification of knowledge) of forensic science claims. This paper focuses on an integrated narrative review using hermeneutic methods of analysis to identify: (i) the epistemic state of forensic science; (ii) strategies to increase of knowledge; (iii) the need for collaboration between practitioners and academics; and, (iv) areas for future research.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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