"Almost islands": A research synthesis of Aboriginal communities in Canada as metaphorical islands
Bibliographic record
Abstract
The purpose of this study is to describe the geographic distribution of Aboriginal people who live in remote, isolated Aboriginal communities in Canada in terms of how geographic settings and features, particularly those that are characteristic of island dwellers, are related to and can impact aspects of culture and identity. Through this process, data was collected using a research synthesis, which allowed for a great deal of data from various sources to be analyzed, extracted, and coded. Based on this qualitative study, numerous geographic characteristics similar to those of islanders and islands emerged. Physically, islands and Aboriginal communities represent bounded, finite spaces that are located on the periphery and are impacted by isolation. These unique isolated areas allow for islanders and Aboriginal people to experience ethnic homogeneity and strong attachments to place, both of which allow for the preservation of culture and identity. That being said, islanders and Aboriginal people both experience migration as a way of life, and leaving their places of origin to experience life in larger, more diversely and densely populated areas is necessary for many. As a result of these findings, this study compares isolated Aboriginal communities in Canada and Aboriginal people to various small islands around the world as well as islanders, through various spatial metaphors.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.027 | 0.017 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".