The Pull of the Stars: Reflections on the Perinatal Experience from Pandemic (1918) to Pandemic (2019)
Bibliographic record
Abstract
Global pandemics have been increasing in frequency over the past several decades, with infectious diseases constituting the third leading cause of death worldwide. Emma Donoghue, in her novel The Pull of the Stars, tells the story of Nurse Julia Power, working in an Irish maternity ward at the height of the 1918 influenza pandemic. During a period of three days, she is responsible for caring for expectant women with influenza who are quarantined together. In this paper, we draw on themes from this novel, employing Heideggerian and Gadamerian hermeneutic tenets as a central approach for analysis and interpretation. The perinatal experience for those described in the novel, as well as a century of experience for women and nurses, underscore the profile of the perinatal realm, and its implied meaning for Dasein. We describe experiences of maternity care as described in the Canadian Nurse journal (1905 to 2019), which contribute to a context of both evolving and unchanging conditions. We identify themes relating to practices of infection control, privacy, dignity, and holistic care and integrate these ideas in the discussion. The historical and contemporary ethical and practice tensions bear consideration for emerging and future impacts from the COVID-19 pandemic on nurses, families, and perinatal nursing practice.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.030 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".