Communication access, public health information sources, and language preference during the COVID-19 pandemic in Indigenous communities in Northwest Territories, Canada
Bibliographic record
Abstract
Effective communication during a public health emergency, such as the COVID-19 pandemic, has been identified by the World Health Organization as a challenge; it is also critical to ensuring more positive public health outcomes. As such, given the already limited health resources available in remote communities, this project aimed to explore communication access, sources of COVID-19 information, and language preference among Indigenous communities in Northwest Territories, Canada. Data collection occurred between April-November 2021 in ten Northwest Territories communities. Utilizing convenience sampling methods due to public health restrictions, self-identifying Indigenous adults (≥18 years) were invited to complete a semi-structured interviewer administered questionnaire. During interviews, relevant public health measures were upheld (i.e., wearing masks and maintaining distance). Open-ended questions regarding communication access, sources of COVID-19 information, and language preference were asked. Results Participants (n = 287; 31.1% male; mean age 41.6 years, SD = 13.5) reported accessing three main forms of communication: radio (84.7%), the internet (80.5%), and cable television (71.8%). Some participants (19.5%) reported having no internet access at home. Participants’ main sources of COVID-19 information were websites (35.3%), social media (26.5%), and the news delivered via television or newspaper (48.4%). Only 11.0% of participants acquired information from healthcare workers. Some participants (9.9%) preferred to receive information in the traditional languages of the Dene (Dene Ked’e, Tłıchǫ) and Anishinaabe. Ensuring communication access by providing adequate internet access in all communities and producing information sources in preferred languages should be a priority. These results can inform future public health policy for Northwest Territories.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".