Delayed motherhood: understanding the experiences of women older than age 33 who are having abortions but plan to become mothers later.
Bibliographic record
Abstract
OBJECTIVE: To examine the experiences of women who are delaying motherhood by having abortions. DESIGN: Mixed-methods study. SETTING: An abortion clinic in Vancouver, BC. PARTICIPANTS: Women presenting for abortion at an urban, free-standing abortion clinic. Interviews were only with women older than 35 years of age. METHODS: A chart review was initially performed, followed by a survey of women presenting to the clinic, as well as in-depth interviews that were audiotaped and transcribed. MAIN FINDINGS: Of the 1844 charts reviewed, 550 (30%) were for women 33 years of age and older and 117 (21%) of those had no children (6% of the total 1844). Plans for future pregnancies were reported in only 70 of the 117 charts; 37 (53%) of the women said they wanted children in the future and 20 (29%) said they were unsure. There were 1118 questionnaires completed (response rate of 86%). There were 334 (30%) women 33 years of age and older and 87 (26%) of those had no children (8% of the total 1113). Of these women, 47 (54%) planned to have children in the future and 24 (28%) were unsure. The most common reason these older childless women gave for having abortions was that they were "just not ready" (59%). We used logistic regression to examine predictors for delaying motherhood and the stepwise regression retained only 2 factors: high rating of "stable relationship" (P=.003) and a "partner who would be a good parent" (P=.008). The most striking themes in the interviews were women's uncertainty about childbearing and their focus on the quality of their relationships. CONCLUSION: This study contributes additional insight into the uncertainty older nulliparous women experience about childbearing, and it points to women's primary focus on relationships with partners rather than with children as a possible explanation for this trend.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".