Towards a Comprehensive Understanding of Fertility

The Model of Dyadic Pathways

Bibliographic Data

ID2428852
AuthorsUta Brehm (0000-0001-5784-9310, Federal Institute for Population Research, corresponding author), Norbert F Schneider, Norbert Schneider (0000-0002-9239-0610, Federal Institute for Population Research)
Year2019
Volume44
Publication date2019-02-05
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueComparative Population Studies (JOURNAL)
Journal identifiersISSN: 1869-8980 • E-ISSN: 1869-8999
PublisherGerman Federal Institute for Population Research (PUBLISHER)
DOI10.12765/cpos-2019-01
OpenAlexW4251657457
LanguageEN
Citations received6
References cited34

In this theoretical contribution, we propose a comprehensive and integrative heuristic model to explain fertility, the Model of Dyadic Pathways (MDP). We show how existing models such as the Theory of Planned Behaviour often do not withstand empirical challenges, especially not individual self-reports in qualitative studies. Furthermore, existing models vary in their premises and foci, resulting in a collection of models which do not necessarily align with or supplement one another. For these reasons, these heuristic models have been widely criticised and, in practice, pieced together according to the research question and tradition of the researcher. Against this backdrop, we establish the MDP to reconnect theory with reality and to unify a variety of approaches. The MDP is grounded on the dyad of partners as the prevalent basis of fertility. It integrates reasoned and unreasoned fertility behaviour, the impact of individual- and couple-level life course, soci(et)al conditions, and the body as an 'actor'. The model explicitly accounts for the variety of different real-life pathways that lead to fertility. It thereby encourages researchers to, first, consider all potentially relevant factors and their mechanisms and, second, think of fertility and its measurement as a multilinear process. Based on the presented elements a comprehensive model of fertility must cover, we suggest ways to improve surveys accordingly. Furthermore, we elaborate on the contributions and challenges the MDP presents to future fertility research

Dyad · Economics · Fertility · Heuristic · Management science · Population · Process (computing · Sociology · Variety (cybernetics · Computer Science · Family Dynamics and Relationships · Psychology · Social Psychology · Artificial Intelligence