Measurement of climate change-related food (in)security and food sovereignty in Canada’s northern communities and the circumpolar region: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Climate change impacts the circumpolar region (including northern Canada) at a greater magnitude than other parts of the world. This affects food (in)security as well as food sovereignty. This scoping review aims to map the methods of measuring food (in)security and food sovereignty across northern Canada and the circumpolar region in support of the Yukon Government's climate change adaptation strategy. METHODS AND ANALYSIS: We will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews, and work will be conducted according to the Joanna Briggs Institute (JBI) manual chapter on scoping reviews. Academic librarians develop the academic literature and grey literature search strategies, and the search strategies are further revised through iterative stages of peer review. The search strategy includes 7 academic literature databases, 11 grey literature databases, over 50 websites and the University of Toronto Libraries catalogue. Covidence, an evidence synthesis software, will be used for screening and extraction. The extraction chart will be developed and piloted by our team. A minimum of two reviewers will conduct screening, and conflicts will be resolved through discussion. Data will be extracted by one reviewer and verified by a second. Conflicts will be resolved through discussion or by a third reviewer. ETHICS AND DISSEMINATION: This project does not require ethical approval as it is secondary research; data will be extracted from published academic research papers, dissertations, and publicly available reports and documents. Our dissemination plan includes presentations at conferences, submission to international peer-reviewed journals and a workshop on the search strategies.
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 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 | 0.148 | 0.131 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.050 | 0.015 |
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".