A Story That Carried Me with It: An Exploratory Analysis of COVID-19 Information Sources among Members of Six Nations of the Grand River
Bibliographic record
Abstract
Introduction: Throughout the COVID-19 pandemic, Indigenous people reported receiving their COVID-19 information from various sources, including friends, family, and community-developed resources. When evaluating the information that they trust the most, it is crucial to consider the complex & dark history that has shaped the reputation of the healthcare system for many. This thesis explored how community members of the Six Nations of the Grand River (SN) First Nations Reserve received and interpreted information relating to the pandemic. There exists no identified evidence that explores how Indigenous people from SN explored, navigated, or interpreted health communication throughout the pandemic. Research Questions: 1) Do different sources of COVID-19 information influence health perceptions or behaviours among members of the SN community?; 2) What factors influence individuals’ choices of specific COVID-19 information sources among members of the SN community? Methods: These questions were answered using descriptive statistics and a nominal logistic regression model. To complement this, I tied the results to their lived experiences working within the community grounded in anecdotal evidence gathered from community members and SN staff during the pandemic. Results: Participants who reported primarily relying on personal networks or social media for their COVID-19 information were less likely to perceive COVID-19 as a serious threat to the community or engage in protective behaviours such as masking and vaccination. The regression highlighted that higher education and income levels were associated with a lower RRR of relying on social media or personal networks compared to governmental sources (e.g., people with a bachelor’s degree (compared to less than high school) had an RRR of 0.11 [0.037-0.31] for choosing personal networks as their primary information choice). Conclusion: This thesis highlights the importance of trust, lived experience, & cultural relevance in supporting community members to make informed health decisions for themselves, their community, and their families.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".