Neurolaw: potential applications of fMRI in courts
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
Functional magnetic resonance imaging (fMRI) is a neuroimaging technique used to study cognitive functions. Despite fMRI having successfully been used to identify many cognitive capabilities, recent research has not found any successful submissions of fMRI evidence in criminal courts in Australia, Canada, England and Wales. Neurolaw is an interdisciplinary area involving neuroscience, law, and philosophy. Publications in neurolaw and research investigating the applications of fMRI in the legal context are increasing. One probable explanation for the lack of admissions of fMRI in the courts is that this is due to the numerous limitations of fMRI. However, many potential applications of fMRI have been recommended. These include lie detection, testing of guilty knowledge, and mind reading. After evaluating the medical uses of fMRI, analysing court cases involving functional neuroimaging evidence and considering the history of imaging evdence,my thesis identifies several potential areas where fMRI might be applicable within the legal context. My study also suggests a hypothetical case that supports a conceptual claim that fMRI migh have potential to be useful in court. Moreover, the hypothetical case supplies a few directions for further study.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.007 | 0.001 |
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