MétaCan
Menu
← Back to cohort
Record W4234313848 · doi:10.24124/2020/59064

Fishing for meaning: creating a nature therapy guided fly-fishing program for students in the learning support center at Prince George Secondary School

2020· dissertation· en· W4234313848 on OpenAlexaffabout
Ryan McIndoe

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of CalgaryUniversity of Northern British ColumbiaUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsGeorge (robot)CurriculumMeaning (existential)Social connectednessMental healthMedical educationPedagogyPsychologyMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Developing high school curriculums that promote positive mental health by fostering connection and meaning is an important undertaking. This project explores the role that Nature Therapy and trauma informed practice can play in guiding curriculum development. To do this the contextual realities the Learning Support Center at Prince George Secondary School are explored and a brief literature review on the topics of Nature Therapy and adolescent based Trauma counselling is completed. The final component of this project is the completion of a School District 57 Board Authorized Course Template that integrates elements of Nature Therapy, trauma informed practice and school connectedness with curricular content.

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)0.001
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: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.024
GPT teacher head0.350
Teacher spread0.327 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same topicUrban Green Space and Health→French-language works237,207→