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Record W4388940465 · doi:10.32920/24624657

Philosophy of Hope

2023· preprint· en· W4388940465 on OpenAlexaff
Michael Milona

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsValue (mathematics)EpistemologyVirtueNatural (archaeology)Set (abstract data type)PhilosophyComputer scienceHistory

Abstract

fetched live from OpenAlex

The philosophy of hope centers on two interlocking sets of questions. The first concerns the nature of hope. Specific questions here include how to analyze hope, how hope motivates us, and whether there is only one type of hope. The second set concerns the value of hope. Key questions here include whether and when it is good to hope and whether there is a virtue of hope. Philosophers of hope tend to proceed from the first set of questions to the second. This is a natural approach, for one might expect that you must develop a basic understanding of what hope is before you can determine its value. The structure of this chapter thus follows this approach. But readers should not be misled: there is in fact a good deal of feedback between the two sets of questions. A theory of hope is more plausible to the extent that it fits well with plausible ideas about the value of hope. So the movement from hope’s nature to its value is one of emphasis rather than a strict, step-wise process.

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)0.004
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.023
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.002

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 head0.066
GPT teacher head0.343
Teacher spread0.278 · 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
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

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