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Record W2589380427

Counselling Children After Wildfires: A School-Based Approach

2017· article· en· W2589380427 on OpenAlexaffvenueabout
Blythe Shepard, Judith C. Kulig, Anna Pujadas Botey

Bibliographic record

VenueCanadian Journal of Counselling and Psychotherapy · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsAlberta Health ServicesUniversity of Lethbridge
Fundersnot available
KeywordsNatural disasterPromotion (chess)PopulationPsychologyGeographyMedical educationMedicineEnvironmental healthPolitical scienceMeteorology
DOInot available

Abstract

fetched live from OpenAlex

Population growth into wildland-urban interface areas and wildland fires continue to threaten people and property across Canada. This article focuses on the promotion of healing of children affected by wildfires based on results from our mixed methods study outlined in detail previously (Townshend et al., 2015). A brief review of the literature on children and their responses to natural disasters and to wildfires is followed by key findings from our research. School counselling strategies are outlined that can be implemented school wide (i.e., universal programs, support groups, or in the classroom) or through individual or group counselling.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0070.002
Scholarly communication0.0020.002
Open science0.0020.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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

Citations8
Published2017
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Counselling and PsychotherapySame topicFire effects on ecosystemsFrench-language works237,207