On the path to reclaiming Indigenous midwifery: Co‐creating the Maternal Infant Support Worker pilot program
Bibliographic record
Abstract
OBJECTIVE: The aim of the Maternal Infant Support Worker (MiSW) pilot program was to implement a virtual training program for lay maternal-infant health providers in remote First Nations communities in Northwestern Ontario, Canada. METHODS: The MiSW pilot program was administered jointly by a community college and a university and consisted of a 20-week virtual course followed by a 9-month mentored work placement in the community. RESULTS: The MiSW pilot program was delivered successfully; 11 of 13 participants received a certificate from a community college. MiSWs provided culturally and linguistically appropriate care to women, infants, and families in their respective communities. MiSWs provided doula support in their communities-a first for our region since the policy of forced evacuation for birth was implemented. MiSWs developed a community of practice for ongoing education, as well as to support each other in their work. CONCLUSION: The MiSW pilot program demonstrated that it is possible to provide a virtual training program and then provide continued virtual mentorship as the participants work in their First Nations communities. By prioritizing Indigenous voices above those of the research team, we were able to gain the trust of the MiSWs and maintain engagement with communities.
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 | 0.010 | 0.009 |
| 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 | 0.001 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".