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Record W4250577418 · doi:10.1089/eco.2009.0036

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2009· article· en· W4250577418 on OpenAlexaboutno aff
Maggie Ziegler

Bibliographic record

VenueEcopsychology · 2009
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsnot available
Fundersnot available
KeywordsWildernessWitnessNarrativeCommitGriefAestheticsPersonal narrativeValue (mathematics)SociologyAccident (philosophy)HistoryPsychologyEnvironmental ethicsLawPsychotherapistArtPolitical scienceEpistemologyPhilosophyEcology

Abstract

fetched live from OpenAlex

This is a personal narrative of a backpacking trip into the remote mountains that form the backbone of Vancouver Island. It is not a commentary on the value of wilderness experience or therapy, or on what defines notions of wilderness; rather the author, a trauma psychotherapist working with victims of violence, is simply telling a story of journeying into the mountains, accompanied by the pain of being a witness to the grief that this world suffers. As she traverses the ridges, she pays careful attention to her inner landscape of violence and loss and to the external landscape of coastal alpine. The necessity for mindful attention brings her step by step to a deeper place, a place of increasing spaciousness and a sustaining unity. Implicit in the narrative are themes of the interconnectedness of all life, what it means to find our place in the world, and loosening the edges between the self and the rest of life. In the mountains, the author is reminded of her true nature and what it means to live awake in the moment, to commit to what needs to be done.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.260
Threshold uncertainty score0.871

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0130.002
Scholarly communication0.0060.003
Open science0.0010.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.2600.096

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 head0.018
GPT teacher head0.380
Teacher spread0.362 · 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 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

Citations1
Published2009
Admission routes1
Has abstractyes

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