Covid-19 Pandemic, Isolation and Birth: An Analysis of the Experiences of Women Having Given Birth during this Period in Quebec
Bibliographic record
Abstract
The health restrictions surrounding pregnancy, birth, and postnatal care imposed during the COVID-19 pandemic have exacerbated the fears and difficulties generally associated with maternity. Since little research has been done, we wished to better understand the consequences of these changes on the maternity experience of Quebec women. During our qualitative research, we analyzed the experiences of Quebec women who went through pregnancy, birth, and postpartum amid the pandemic. These experiences were shared in 366 posts selected from four Facebook groups on maternity and through 20 semi-structured interviews. The data derived from this convenience sample were analyzed following a non-linear trajectory where data collection was interspersed with analysis sessions. For the women involved in this research, the pandemic has mainly impacted (1) their perception of what constitutes a normal experience of maternity care; (2) their perceived need for support and services to address the risks related to the pandemic; and (3) what they consider symbolic milestones associated with maternity. Our findings underscore the significance of considering the interpretation attributed to care and services amidst alterations or interruptions (as was the case during COVID-19). The backdrop of the global crisis has caused women to perceive a sense of incompletion in their experience of maternity through the loss of certain key moments, and even to look to the future with trepidation. Consequently, we anticipate enduring ramifications arising from the pandemic, and we encourage healthcare personnel to remain attentive towards women who have given birth during this period of crisis. The notion of ‘normal’ maternity can be associated with a medicalized period. While motherhood can disrupt many aspects of women’s lives, socio-cultural expectations surrounding the process can help them navigate certain challenges. However, times of crisis inherently disrupt normalcy and require populations to undergo adaptations that can reshape their worldviews. This research examines the intersection between ‘crisis periods’ and ‘maternity periods’. It offers an innovative and interdisciplinary analysis (psychology, midwifery, socio-anthropology, and communication) and highlights a unique situation where the disruption of a deeply entrenched sociocultural context has resulted in varied consequences on women’s maternity experiences.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".