MétaCan
Menu
Back to cohort
Record W3022921090 · doi:10.1111/ejop.12542

Why you cannot make people better by telling them what is good

2020· article· en· W3022921090 on OpenAlex
Ulf Hlobil

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

VenueEuropean Journal of Philosophy · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsConcordia University
Fundersnot available
KeywordsCeteris paribusPessimismOptimismTrustworthinessCore (optical fiber)Social psychologyPsychologyPositive economicsLaw and economicsEpistemologySociologyEconomicsPhilosophy

Abstract

fetched live from OpenAlex

Abstract So‐called optimists about moral testimony argue, against pessimists, that, ceteris paribus, we ought to accept and act in accordance with trustworthy, pure moral testimony. I argue that even if we grant this, we need to explain why moral testimony cannot make us more virtuous. I offer an explanation that appeals to the fact that we cannot share inferential abilities via testimony. This explanation is compatible with the core commitments of optimism, but it also allows us to see what is right about pessimism.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.534
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.007
Insufficient payload (model declined to judge)0.0020.002

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 head0.121
GPT teacher head0.382
Teacher spread0.262 · 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