MétaCan
Menu
Back to cohort
Record W6964491707 · doi:10.25384/sage.c.7248512.v1

Promoting health and wellness through Indigenous sacred sites, ceremony grounds, and land-based learning: a scoping review

2024· other· en· W6964491707 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2024
Typeother
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousCeremonyTraditional knowledgeHealth promotionPromotion (chess)Grey literaturePublic health

Abstract

fetched live from OpenAlex

This study analyzes the literature on Indigenous sacred sites within the larger topic areas of land-based education and healing, as per the guidance of Anishinaabe (a group of Indigenous Peoples from the Great Lakes and the Great Plains areas of contemporary Canada and USA) Elders and community leaders in eastern Manitoba, Canada. A scoping review was conducted to identify the size, scope, nature, and key themes of existing research in seven databases, inclusive of gray literature which is a key source for Indigenous organizations. In total, we analyzed 35 articles and documents. The emerging themes included: (1) sacred sites and the promotion of health and wellness; (2) sacred sites as places of knowledge; (3) the desecration and protection of sacred sites; and (4) legal battles between Indigenous Peoples and the state. Recommendations to advance understandings and correct colonially imposed imbalances are discussed, and health and legal implications are outlined.

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)0.008
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0170.021
Science and technology studies0.0020.002
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.067
GPT teacher head0.327
Teacher spread0.260 · 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 designSystematic review
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueSage Journals DataSame topicEcology and biodiversity studiesFrench-language works237,207