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Record W4313412563 · doi:10.3998/ergo.2234

Hope as a Source of Grit

2022· article· en· W4313412563 on OpenAlexaff
Catherine Rioux

Bibliographic record

VenueErgo an Open Access Journal of Philosophy · 2022
Typearticle
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsGritHopefulnessRationalityAction (physics)Agency (philosophy)EpistemologyDimension (graph theory)Psychological resiliencePsychologySociologySocial psychologyPositive economicsEconomicsPhilosophyMathematics

Abstract

fetched live from OpenAlex

Psychologists and philosophers have argued that the capacity for perseverance or “grit” depends both on willpower and on a kind of epistemic resilience. But can a form of hopefulness in one’s future success also constitute a source of grit? I argue that substantial practical hopefulness, as a hope to bring about a desired outcome through exercises of one’s agency, can serve as a distinctive ground for the capacity for perseverance. Gritty agents’ “practical hope” centrally involves an attention-fueled, risk-inclined weighting of two competing concerns over action: when facing the decision of whether to persevere, hopeful gritty agents prioritize the aim of choosing a course of action which might go very well over that of choosing a course of action which is very likely to go fairly well. By relying on the notion of a “risk-inclined attentional pattern” as a dimension of gritty agents’ practical hope, we can explain that form of hope’s contribution to their motivation and practical rationality, especially on a risk-weighted expected utility framework. The upshot is a more pluralistic view of the sources of grit.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.067
GPT teacher head0.410
Teacher spread0.343 · 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 teacher head, not a consensus.

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

Citations8
Published2022
Admission routes1
Has abstractyes

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