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Record W4407428002 · doi:10.7202/1115461ar

Neither “True Being” nor “Cosmic Pyrotechnics”: Dewey’s Naturalistic Metaphysics as Environmental Pedagogy Aid

2024· article· en· W4407428002 on OpenAlexvenueno aff
Sarah Warren

Bibliographic record

VenuePhilosophical Inquiry in Education · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicPragmatism in Philosophy and Education
Canadian institutionsnot available
Fundersnot available
KeywordsNaturalismMetaphysicsCOSMIC cancer databaseEnvironmental educationEpistemologyCurriculumPedagogyPhilosophyPsychologyPhysicsAstronomy

Abstract

fetched live from OpenAlex

Drawing primarily on John Dewey’s Experience and Nature, but putting his metaphysical commitments into conversation with pedagogical experience, this article asks: how might a Deweyan understanding of nature and our experience within it support environmental progress? More specifically, how might we respect pluralistic relationships with philosophy in the classroom while simultaneously cultivating an understanding of experience that clarifies the embodied nature of our meaning-making within it and the contextual urgencies of today? How might observing the “generic traits of existence” and their particular and qualitative manifestations foster an appreciation for how the natural world acts as wellspring of human values? For Dewey as well as William James, experience is “double barreled,” designating both the “planted field” and “the one who plants and reaps”: functional distinctions serve a purpose, but experience emerges at, and astride the tensional energies that characterize, the permeable boundaries of self and world. Taking Dewey’s insights to heart illuminates how issues like biodiversity preservation are deeply existential concerns that are ripe for a Deweyan pedagogical intervention.

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)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.071
Scholarly communication0.0070.013
Open science0.0010.006
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.322
Teacher spread0.284 · 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
Published2024
Admission routes1
Has abstractyes

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