From the Profound to the Mundane

Questionnaires as Emerging Technologies in Autism Genetics

Bibliographic Data

ID5337684
AuthorsG Hollin (0000-0003-4348-8272, University of Leeds)
Year2019
Volume44
Issue4
Pages634-659
Publication date2019-07-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueScience Technology & Human Values (JOURNAL)
Journal identifiersISSN: 0162-2439 • E-ISSN: 1552-8251
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/0162243919841691
OpenAlexW2939647749
LanguageEN
Citations received1
References cited84

It is widely argued that the final decades of the twentieth century saw a fundamental change, marked by terms such as biomedicalization and geneticization, within the biomedical sciences. What unites these concepts is the assertion that a vast array of emerging technologies-in genomics, bioengineering, information technology, and so forth-are transforming understandings of disease, diagnosis, therapeutics, and working practices. While clearly important, these analyses have been accused of perpetuating theoretical trends that attribute primacy to the new over the old, discontinuity over continuity, and the laboratory over the field. In this paper, I show that in the case of autism, the effects of genomic technologies can only be understood by simultaneously examining the role of questionnaires. Due to shortcomings in clinical diagnoses, genomic analyses could only progress once questionnaires had been developed to address a "reverse salient" within the "technological system." Furthermore, I argue that questionnaires such as the Autism Quotient have a significance that surpasses the genomic classifications they were designed to undergird. I argue that to neglect the role of mundane technologies such as questionnaires in contemporary biomedicine is to miss complexity, bifurcate old and new, and do a disservice to innovation

Assertion · Autism · Data science · Developmental psychology · Emerging technologies · Engineering ethics · Epistemology · Neglect · Paradigm shift · Political science · Psychiatry · Salient · Sociology · Autism Spectrum Disorder Research · Computer Science · CRISPR and Genetic Engineering · Engineering · Genomics and Rare Diseases · Law · Psychology · Artificial Intelligence

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