Pregnant Canadians and Public Health Communication During the Early Pandemic
Bibliographic record
Abstract
Background: Pregnant Canadians have particular information needs during a public health crisis. Duringthe COVID-19 pandemic, participants relied on their primary care providers in the absence of clear publichealth messages that focused on the context of pregnancy and the needs of pregnant people.Methods: A qualitative study in which pregnant Canadians wrote journal entries about their careexperiences in response to prompts during the early COVID-19 pandemic.Findings: Participants were cared for by a range of primary care provider types. Those seeing midwiveshad the most positive experiences with seeking information related to how the pandemic would affect theirlives and pregnancies. However, it was also clear that the absence of provincial and federal messagingdirected towards pregnant people created the potential for inconsistency and harms. RESUME Contexte : Au Canada, les personnes enceintes ont besoin de renseignements bien particuliers durantune crise de santé publique. Pendant la pandémie de COVID-19, les personnes participantes se sont fiéesà leurs fournisseurs de soins primaires en l’absence de messages de santé publique clairs axés sur lagrossesse et les besoins des personnes enceintes.Méthodes : Une étude qualitative a été réalisée au cours de laquelle des personnes enceintescanadiennes ont écrit dans leur journal leurs expériences de soins en réponse à des invites au début de lapandémie de COVID-19.Constatations : Les personnes participantes ont été soignées par une diversité de types de fournisseursde soins primaires. Celles qui ont consulté des sages-femmes ont connu les expériences les plus positiveslorsqu’il s’agissait d’obtenir des renseignements sur l’incidence possible de la pandémie sur leur vie et leurgrossesse. Cependant, il était également évident que l’absence de messages des gouvernements fédéralet provinciaux destinés aux personnes enceintes a constitué une source possible d’incohérence et depréjudices.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.031 | 0.010 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".