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Record W3095501661 · doi:10.1177/1053825920967034

Character Through Outdoor Adventure Education? The (Delimiting) Hope of Modern Virtue Ethics

2020· article· en· W3095501661 on OpenAlexaff
Paul Stonehouse

Bibliographic record

VenueJournal of Experiential Education · 2020
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVirtueVirtue ethicsCharacter (mathematics)AdventureCharacter educationSociologyEnvironmental ethicsMoral characterSituationismCriticismEpistemologyAdventure educationAestheticsOutdoor educationPedagogyLawPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Background: The long-held assumption of character development through outdoor adventure education (OAE) maintains some adherents; however, growing criticism calls into question its efficacy. Yet, current social/environmental crises signal the immediate importance of moral education. Purpose: This article highlights the importance of character in moral assessment and guidance and registers the need for an account of character relevant to OAE’s social/environmental aims. It suggests a modern virtue ethical lens as a philosophical and practical way forward for OAE’s moral educational mission. Methodology/Approach: This article searches the OAE literature for substantiating evidence (rational and empirical). Then, in light of this search, a virtue ethical account of character, including its development, and relevance to OAE, is outlined. Findings/Conclusions: Evidence for character development through OAE is nearly non-existent, and semantic, philosophical, and empirical critiques loom large. If OAE wishes to continue its moral mission, then an account of character—promisingly provided in virtue ethical theory(s)—that can withstand these critiques is needed. Implications: Applied to OAE, modern virtue ethical theory provides an account of character, copes with the critiques, and supplies socially/environmentally relevant curricular and pedagogical guidance for future practice, while likely delimiting our claim to character development.

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)0.000
metaresearch head score (Gemma)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.387
Teacher spread0.345 · 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 designQualitative
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

Citations2
Published2020
Admission routes1
Has abstractyes

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