Bibliographic record
Abstract
PURPOSE OF REVIEW: Although there has been an increase in research on postpartum depression (PPD), an inadequate focus has been placed on immigrant women. This is a significant limitation given the rapidly changing demographics in North America. RECENT FINDINGS: Immigrants face unique and multiple layers of challenges that may compromise their mental health and prevent them from receiving adequate and equitable care. For immigrant women, many of these stressors are especially compounded in the vulnerable postpartum period, resulting in PPD. Cultural values and practices may be protective in some instances, whereas in other instances they exacerbate PPD. There is a significant gap in existing literature regarding the complex psychosocial, cultural, and spiritual factors that may moderate the effects of the depression. Furthermore, the measurement of PPD is hampered by cross-cultural methodological challenges. SUMMARY: Given the complexity of the psychosocial issues facing immigrant women, there is a need to develop a comprehensive response toward addressing the multifaceted challenges, ensuring equitable immigration and related policies; adequate community resources and social services to address social determinants of health; inclusiveness in public health and prevention strategies; equitable access to a culturally competent healthcare system; capacity building of marginalized communities; and culturally competent interventions at the individual level. Additional research using the bidimensional model of acculturation is needed.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".