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Record W2913194095 · doi:10.1017/s1352325218000186

GROUNDING PROCEDURAL RIGHTS

2019· article· en· W2913194095 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

VenueLegal Theory · 2019
Typearticle
Languageen
FieldNeuroscience
TopicFree Will and Agency
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSkepticismHarmPunishment (psychology)Subject (documents)Law and economicsPolitical sciencePunitive damagesLawPsychologyPhilosophySociologyEpistemologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

Abstract It is commonly held that we wrong someone if we punish them without first determining whether they are guilty through the process of a sufficiently fair and reliable procedure. This wrong is best explained by pre-institutional moral procedural rights. Recently, Christopher Heath Wellman has argued for the skeptical conclusion that there are no such rights, challenging a widely held orthodoxy. I propose two novel grounds for pre-institutional moral procedural rights and so answer Wellman's skepticism. First, we have rights not to be subject to punitive systems that do not include specific sorts of reliable procedures because otherwise we are subject to unreasonable risks of undeserved punishment. Second, not only do we have rights that others not harm us or unreasonably risk harming us, we have rights that they control for avoiding wrongfully harming us across relevant close possible worlds.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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