Two-Eyed Seeing for Parents: Developing an App for Parents in the syilx Okanagan First Nation
Bibliographic record
Abstract
This paper describes development of an offline app entitled Two-Eyed Seeing for Parents, which promotes syilx Okanagan Territory parents’ knowledge, confidence, and cultural practices for supporting optimal infant development, including exposure to their traditional language (nsyilxcən). “Two-Eyed Seeing” blends Indigenous and Western epistemic principles (syilx traditions complemented and supported by evidence-based content). Elders, members of the səxʷkn̓xitəlx k̓l̓ c̓əc̓málaʔ Early Years Table, and University of British Columbia researchers partnered to develop the offline app. The Table is committed to improving the well-being of syilx Okanagan Territory children. An Elder representing the Table signed a university cooperative research protocol agreement with one researcher. The agreement required signatories to adhere to principles of free, prior, and informed consent and Indigenous ownership, control, access, and possession and specified that the səxʷkn̓xitəlx k̓l̓ c̓əc̓málaʔ Early Years Table retained the exclusive ownership of and right to reproduce Indigenous knowledge in the app. Elders decided on content and organization of the app and crafted additional information to reflect community priorities. The content incorporates some elements of SmartParent, an evidence-based online SMS app. The offline app clusters resources by months of infants’ first years of life and by topic (including parents’ and infants’ emotional, physical, and spiritual needs, and mental and physical aspects of parenting). It contains original recordings of nsyilxcən language and extensive First Nations materials. Memotext created the app architecture. Elders and Table Members approved the final offline app version. The app offers syilx parents continuous access to culturally grounded information and overcomes problems with Internet access and prohibitive data costs to access links.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".