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Record W3157166901 · doi:10.1163/18756735-000108

The Worst Things in Life

2020· article· en· W3157166901 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

VenueGrazer Philosophische Studien · 2020
Typearticle
Languageen
FieldNeuroscience
TopicFree Will and Agency
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTest (biology)Completeness (order theory)Experiential learningCover (algebra)WelfareEpistemologyPsychologyPhilosophyMathematicsLawMathematics educationPolitical science

Abstract

fetched live from OpenAlex

Abstract One important test of adequacy for a theory of welfare is completeness. To be complete a theory must cover ill-being as well as well-being. Call this the ill-being test for a theory. The author’s aim in this article is to determine how well equipped the leading theories of welfare are to pass this test. The author reaches three modest conclusions: (1) passing the test is not straightforward for any theory; (2) on the whole, subjective theories do better than objective ones; (3) within the subjective category experiential theories do better than desire theories.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.678
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.088
GPT teacher head0.256
Teacher spread0.168 · 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