Niicugnissuun/Tuu'awinpi: Tribal Radio as a Unique Community Medium and a Source of Health Information for Rural Indigenous Communities
Bibliographic record
Abstract
Indigenous peoples in the United States experience some of the most severe health inequities out of any racial/ethnic group, and are simultaneously affected by significant barriers to accessing information. This dissertation presents a community-based participatory research project on the role of tribal radio as a unique community medium and a source of health information for rural Indigenous communities. In addition to learning about tribal radio as a health information resource, this study also characterizes tribal radio in detail, a severely understudied medium that remains vital for its audience. The very small body of research that exists on tribal radio has focused on its role in revitalizing Indigenous languages. While this is an important contribution that is also discussed here, this study revealed a multitude of other functions and characteristics of tribal radio that set it apart from other community media. The project was conducted in partnership with two prominent tribal radio stations: KYUK in Bethel, Alaska, the oldest continuously operating tribal station in the U.S., serving a rural population of predominantly Yup’ik subsistence hunters and fishermen in the Yukon-Kuskokwim Delta, and KUYI, located on the Hopi Reservation and serving the Hopi and Tewa people living in the 12 rural villages on the reservation. This is a qualitative study comprised of 12 individual, in-depth interviews (5 with KUYI staff and 7 with KYUK staff) and 7 focus groups (4 with KUYI listeners and 3 with KYUK listeners), totaling 66 participants overall. Using interview data, I first consider the historical ties of tribal radio with the Indigenous activism of the 1970s and the relevance of these historical origins for its functioning today, how station managers and employees aim to realize their missions, how they share health information on their station, as well as the self-concept of Indigenous media practitioners. Findings reveal that tribal radio practitioners view themselves as more than journalists; they have a tremendous sense of accountability to the communities they serve, and see themselves as protectors and an advocates. They act as translators of language, reading levels, and differing cultural norms to try to lower psychological and information-related barriers of healthcare access for their listeners, while raising awareness of common health issues and prevention strategies. Tribal stations also collect and house valuable audio archives of the tribes’ history and culture, and face difficult decisions about which materials are culturally appropriate to be shared publicly or not. The focus group data provides a rare insight into the audience perspective of tribal radio. To the best of my knowledge, no prior research has presented audience data on U.S. tribal radio. For listeners of all age groups, tribal stations are a community gathering space where everyone can speak and participate, and which is an appropriate forum to discuss even difficult or usually taboo health topics together as a community. The audience has tremendous trust in the information shared on their tribal station, and is highly receptive to health information from tribal radio. Even monolingual English speakers strongly support and value Indigenous language programming on tribal radio. Listeners feel empowered in their interactions with healthcare providers and develop a greater sense of a shared Indigenous identity. Tribal radio is a testament to Indigenous resilience, creativity, cultural strength, and reaffirms tribal sovereignty through its existence and programming.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".