Digital Technology Innovations in Education in Remote First Nations
Bibliographic record
Abstract
Using a critical settler colonialism lens, we explore how digital technologies are being used for new education opportunities and First Nation control of these processes in remote First Nations. Decolonization is about traditional lands and creating the conditions necessary so Indigenous people can live sustainably in their territories (Simpson, 2014; Tuck & Yang, 2012). Remote First Nations across Canada face considerable challenges related to accessing quality adult education programs in their communities. Our study, conducted in partnership with the Keewaytinook Okimakanak Research Institute, explores how community members living in remote First Nations in Northwestern Ontario are using digital technologies for informal and formal learning experiences. We conducted an online survey in early 2014, including open-ended questions to ensure the community members’ voices were heard. The critical analysis relates the findings to the ongoing project of decolonization, and in particular, how new educational opportunities supported by digital technology enable community members to remain in their communities if they choose to, close to their traditional lands
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".