Protocol for Scoping Review: Bush foods and food-based cultural activities for the health and wellbeing of First Nations peoples in Australia, New Zealand, Canada, and the United States of America
Bibliographic record
Abstract
ABSTRACT: Introduction: First Nations peoples’ conservation efforts have provided access to nutrient-rich bush foods for sustenance. The health and wellbeing benefits of bush foods and food-based cultural activities for First Nations peoples have been described as extending beyond the effects of nutrient composition, with benefits to identity and connection to culture. The objective of this scoping review is to describe the available literature examining bush foods and food-based cultural activities for the health and wellbeing of First Nations peoples, including consideration of the Indigenist lens in the study design, interventions, and the health and wellbeing outcomes investigated. Inclusion criteria: This scoping review will follow the Joanna Briggs Institute (JBI) methodology for conducting a scoping review using the Population/Concept/Context (PCC) framework. The scoping review will include studies with First Nations peoples as the participants, details of any bush foods, food-based cultural activities, and health and wellbeing outcomes measured. Additionally, the review will include details of the study design, evaluation tools and methodologies. Studies conducted in any setting in Australia, New Zealand, Canada and the United States of America will be eligible for inclusion. Search strategy and synthesis: The scoping review will use a three-step search strategy to locate literature published on several databases from the date of inception, including Medline (Ovid) and Embase (Ovid). Grey literature in the form of reports or evaluations from various government and non-government websites will be included. The scoping review will only include studies published in the English language. Details will be extracted using the Covidence data extraction tool. A narrative description of each included study will be provided, along with mapping and frequency counts of relevant PCC elements. This scoping review will build upon current research by providing insight into the study design, interventions, health and wellbeing measures and the approaches taken to ensure ethical research is conducted with First Nations peoples in the bush foods space.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.106 | 0.146 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.016 | 0.017 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.013 | 0.011 |
| Insufficient payload (model declined to judge) | 0.104 | 0.028 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".