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Record W4383312253 · doi:10.11647/obp.0338.02

2. Having Too Much

2023· book-chapter· en· W4383312253 on OpenAlexfundno aff
Ingrid Robeyns

Bibliographic record

VenueOpen Book Publishers · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
FundersEuropean Research CouncilUniversiteit van AmsterdamUniversiteit LeidenUniversiteit UtrechtYork UniversityLondon School of Economics and Political ScienceUniversity of Victoria
KeywordsArgument (complex analysis)DoctrineReprintEpistemologyLaw and economicsPoliticsPower (physics)PhilosophyDemocracyPositive economicsPolitical scienceSociologyLawEconomicsPhysics

Abstract

fetched live from OpenAlex

This chapter is a reprint of what has become the germinal article on limitarianism. After laying out the distinction between intrinsic and instrumental limitarianism, the first part develops two arguments for limitarianism – the democratic argument, and the unmet basic needs argument. The second part develops a theoretical account of ‘the power of material resources’, which is the metric on which we should put the riches line. Next, the distinction between limitarianism as a moral and a political doctrine is discussed. The chapter closes by responding to two objections to limitarianism.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.064
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.011
Scholarly communication0.0080.014
Open science0.0010.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0640.024

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 head0.153
GPT teacher head0.366
Teacher spread0.213 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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