Authors: Shelley Grant*,
Topics: Medical and Health Geography, Legal Geography, Population Geography
Keywords: assisted reproductive technologies, disease prevention, bioethics, health geographies, legal geographies
Session Type: Paper
Presentation File: No File Uploaded
Regulating fertility preservation implies the need for studied assurances that existing assessments on needs, outcomes and patient experiences lead to ethical reproductive care. Fertility preservation involves freezing healthy sex cells and tissues for use in later childbearing through technologically assisted reproduction (ART). Initially developed in the mid-20th century, recent improvements have prompted interest in expanding preservation beyond cancer survivors and those exposed to fertility-reducing environments. Yet, any policy endorsement of elective preservation or “social freezing” remains questioned. Even in regions reporting high ART activity such as Europe, the 2015 launch of preservation sponsorship by employers was critiqued as perpetuating unethical gender biases (Grant 2016). Less research addresses the inherent biases of methodologies used to create policymaking evidence. Partly addressing this aim, reproductive justice advocates claim that some data practices cause inequities. Yet, their interest-based arguments omit reviews on the moral dimentions of applied inferential methods and the harm of reliance on analytics for policymaking on uncertain health situations. This paper critically reviews policy applications of fertility preservation data. Furthering expert commentaries on predictive ART analyses (e.g. ESHRE, ICMART), this work reads across a “diversity” (Braverman 2014) of past (Warnock 1984), current and proposed (Ruggiu 2019) policymaking approaches to examine “substantive” founding (Dixon and Marsten 2011) issues concerning elective reproductive care. It summarily explores differing descriptions of reproductive choice that serve moral aims and defy health insecurities created by an over-reliance on cutting-edge health informatics (Smith 2000, Lawson 2007).
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