Do People Really Know Their Fertility Intentions? Correspondence between Self-Reported Fertility Intentions and Narratives

Fertility intention data from surveys often serve as a crucial component in modeling fertility behaviors. Yet, the persistent gap between stated intentions and actual fertility decisions, coupled with the prevalence of uncertain responses, has cast doubt on the overall utility of intentions and sparked controversies about their nature. In this study, we use survey data from a representative sample of Dutch women. With the help of open-ended questions (OEQs) on fertility and Natural Language Processing (NLP) methods, we are able to conduct an in-depth analysis of fertility narratives. Specifically, we annotate the (expert) perceived fertility intentions of respondents and compare them to their self-reported intentions from the survey. Through this analysis, we aim to reveal the disparities between self-reported intentions and the narratives. Furthermore, by applying neural topic modeling methods, we could uncover which topics and characteristics are more prevalent among respondents who exhibit a significant discrepancy between their stated intentions and their probable future behavior, as reflected in their narratives.

2. Do People Really Know Their Fertility
Intentions?
Correspondence between Self-Reported
Fertility Intentions and Narratives
Xu Xiao, Anne Gauthier, Gert Stulp, Antal van den Bosch
Edinburgh, Scotland
Jun 13, 2024

3. Background: fertility intention
●Prevalent uncertainty and instability in fertility intentions suggest they are constructed
through time and contextual (Bhrolcháin and Beaujouan 2019, Müller et al. 2022)
●Data collection method on fertility intentions has rarely been evaluated
●Natural Language Processing (NLP) methods enable us to automatically analyze
open-ended data
●Do people’s self-reported fertility intentions correspond with the conditions and
narratives reflected in open-ended answers?

4. Data: open questions
●433 Dutch women between 21-44 in 2021 from LISS panel
●The standard survey question on fertility intention (GGS: FERXX):
○Do you intend to have a child in the next three years?
○If you don't have children for the next three years, would you still plan to
have children after that?
●After the module, we added a follow-up open question*
○Can you tell us more about what makes you (un)certain about whether or
not to have children?
* Questionnaire and responses originally in Dutch.

5. Data: annotation
●Each response annotated by three individuals on our
interpretation of the most likely long-term fertility outcome
●Annotations follow the same scheme as the close-ended
questions
●Results compared to respondents’ self-reported intentions

8. Method: topic modeling and
classification model
●Binomial logistic regression
●Target: whether a respondent’s self-reported long-term fertility
intention is the same as our annotated label
●Features: age, education level, income, partnership, number of
children, topics in open answers (extracted by an NLP model)

9. Intentions match with or deviate from
our estimations

10. Discussion
●Fertility intention often not in line with life conditions
●Uncertainty in existing measurements could be underestimated
●People with strong positive fertility intentions are more likely to
have harder-to-achieve intentions
○health-related issues or being students
●People with strong negative fertility intentions are more likely to
have more realistic expectations

11. Thanks for your attention!
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