On the institutional and intellectual division of labor in epigenetics research: A scientometric analysis is a dataset published in Social Science Information (2020). On theSindex it has a DataRank of 0.940, placing it in the top 42.4% of the data-sharing corpus. It has been cited 20 times, with 17 citing works in its 1-hop citation network.
While numerous qualitative social scientific analyses of (environmental) epigenetics have been published, we still lack a macro-level, quantitative assessment of the field of epigenetics as a whole. This article is aimed at filling this gap. Mobilizing an extended version of the Web of Science, we constituted a corpus of 199,484 documents (articles, reviews, editorial material, etc.) published between 1991 and 2017 and performed several scientometric analyses to map out the development and structure of the epigenetics field. Three main results were drawn from these investigations. First, contradicting the hope expressed by some social scientists that their disciplines will find solace in epigenetics’ social biology, it is striking that the scientists, journals and institutions that drive most of the research in the field are overall little concerned with social and environmental dimensions of gene expression. Second, and confirming existing qualitative analyses, we find that epigenetics is constituted by diverse networks of scholars, institutions and research specialties that enjoy relative autonomy from each other and approach epigenetics through different thematic interests, from cognitive functions to cancer, to DNA methylation in plants and molecular biology. Third, findings obtained from the bibliographic coupling showed that these different networks became more and more autonomous over the last decade, which suggests that we are currently witnessing the constitution of a scientific archipelago akin to that of behavior genetics (Panofsky, 2014: 33) rather than to a discipline per se. At the same time, this differentiation was less pronounced conceptually speaking, as we also observed a clear standardization of the keywords used in epigenetics articles between 1991 and 2017, with DNA methylation and RNAs serving as rallying signs for different communities of researchers.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.449
From this paper's citation signal
Citation Network Contribution
0.490
From 15 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 48% comes from its base citations and 52% from the citation network (15 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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