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Record W3022478239 · doi:10.1080/21548455.2020.1748743

Aboriginal youth summer camp in science and health science: a Western Canadian university review of 10 years of successes and learning

2020· article· en· W3022478239 on OpenAlexaffabout
Naowarat Cheeptham, Star Mahara, Chadabhorn Insuk, Kara Loy

Bibliographic record

VenueInternational Journal of Science Education Part B · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsSummer campHealth scienceScience educationCurriculumSociologyPedagogyMedical educationPsychologyMedicine

Abstract

fetched live from OpenAlex

Over the past ten years, a western-Canadian university has offered an annual on-campus summer science and health science camp for Aboriginal youth. The goal of this camp has been to enhance pathways to science and health science careers for high school students aged 13–15 years-old. The camp's core curriculum exposes youth to science and health sciences through fun and engaging activities. Students consistently reported that the camp helped strengthen connections between their learning in secondary school, potential university level education, and future career options in science and health science. This camp has been well received across British Columbia Aboriginal communities as evidenced by increasing enrollments and community member participation. As faculty and staff involved in the 10-year history of the summer camp, we reflect on our work for the purpose of informing others concerned with promoting science and health science careers for Aboriginal youth. Given a gap in the literature around planning and delivering successful science and health science-focused summer camps for Aboriginal youth, we offer this account of our successes and lessons learned for those planning or already engaged in implementing similar educational efforts.

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)0.013
metaresearch head score (Gemma)0.018
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: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.013
Science and technology studies0.0100.004
Scholarly communication0.0070.002
Open science0.0020.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.141
GPT teacher head0.513
Teacher spread0.372 · 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
GenreReview

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

Citations6
Published2020
Admission routes2
Has abstractyes

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