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Selective Hard Compatibilism

2010· book-chapter· en· W2499612707 on OpenAlexfundno aff
Paul Russell

Bibliographic record

VenueThe MIT Press eBooks · 2010
Typebook-chapter
Languageen
FieldNeuroscience
TopicFree Will and Agency
Canadian institutionsnot available
FundersQueen's UniversityMcGill University
KeywordsCompatibilismPsychologyPhilosophyEpistemologyMoral responsibility

Abstract

fetched live from OpenAlex

Recent work in compatibilist theory has focused a considerable amount of attention on the question of the nature of the capacities required for freedom and moral responsibility.Compatibilists, obviously, reject the suggestion that these capacities involve an ability to act otherwise in the same circumstances.That is, these capacities do not provide for any sort of libertarian, categorical free will.The difficulty, therefore, is to describe some plausible alternative theory that is richer and more satisfying than the classical compatibilist view that freedom is simply a matter of being able to do as one pleases or act according to the determination of one's own will.Many of the most influential contemporary compatibilist theorists have placed emphasis on developing some account of "rational selfcontrol" or "reasons-responsiveness." 1 The basic idea in theories of this kind is that free and responsible agents are capable of acting according to available reasons.Responsibility agency, therefore, is a function of a general ability to be guided by reasons or practical rationality.This is a view that has considerable attraction since it is able to account for intuitive and fundamental distinctions between humans and animals, adults and children, the sane and the insane, in respect of the issue of freedom and responsibility.This an area where the classical account plainly fails.In general terms, rational self-control or reasons-responsive views have two key components.The first is that a rational agent must be able to recognize the reasons that are available or present to her situation.The second is that an agent must be able to "translate" those (recognized) reasons into decisions and choices that guide her conduct.In other words, the agent must not only be aware of what reasons there are, she must also be capable of being moved by them.This leaves, of course, a number of significant problems to be solved.For example, any adequate theory of this Selective Hard Compatibilism

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.033
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.006
Scholarly communication0.0030.009
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0330.003

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 head0.073
GPT teacher head0.249
Teacher spread0.176 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2010
Admission routes1
Has abstractyes

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