MétaCan
Menu
Back to cohort
Record W4407035059 · doi:10.1080/21507740.2025.2450537

From Scholarship to Practice: Standardizing Calls to Action in Neuroethics

2025· article· en· W4407035059 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAJOB Neuroscience · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroethics, Human Enhancement, Biomedical Innovations
Canadian institutionsNeuroDevNetUniversity of British Columbia
Fundersnot available
KeywordsNeuroethicsAction (physics)ScholarshipPsychologyEngineering ethicsNeuroscienceCognitive sciencePolitical scienceLawEngineering

Abstract

fetched live from OpenAlex

A significant goal of neuroethics is to offer neuroscientists, health care providers, law- and policy-makers and others, ways of thinking and acting on matters relevant to brain health and conditions that affect the central nervous system. This goal and related calls to action have been derived from theory or empirical work and bring different levels of normative force. To bring the latter in particular to the foreground of discussion, we explored for this Policy Forum different calls to action as they are associated with chosen terminology, the definitions of terms, origins to which they are benchmarked, locations in text, and targeted audiences. We find variability on all of these factors as they appear in the original foundational journals for neuroethics: AJOB Neuroscience and Neuroethics. We recommend that for a field whose very existence relies on uptake of advice, better consistency of language will improve credibility, acceptance, and implementation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.063
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.063
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.160
GPT teacher head0.472
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it