The structural wings of Matthew effects: The contribution of three-level network data to the analysis of cumulative advantage

The article presents a three-level network approach to the Matthew effect as a multilevel complement to Burt’s (2005) conception of the relationship between networks and performance. We first introduce a three-level dataset and the specificity of this data structure for explorations of cumulative ad...

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Main Authors: Emmanuel Lazega, Marie-Thérèse Jourda
Format: Article
Language:English
Published: SAGE Publishing 2016-02-01
Series:Methodological Innovations
Online Access:https://doi.org/10.1177/2059799115622764
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spelling doaj-ee6801b98b6d4c38b3248f3a6c2020182020-11-25T03:27:47ZengSAGE PublishingMethodological Innovations2059-79912016-02-01910.1177/2059799115622764The structural wings of Matthew effects: The contribution of three-level network data to the analysis of cumulative advantageEmmanuel Lazega0Marie-Thérèse Jourda1Sciences Po-Paris, CSO-CNRS, SPC, Paris, FranceCEPEL-CNRS, Montpellier, FranceThe article presents a three-level network approach to the Matthew effect as a multilevel complement to Burt’s (2005) conception of the relationship between networks and performance. We first introduce a three-level dataset and the specificity of this data structure for explorations of cumulative advantage. Second, we present a population of scientists and provide a heuristic visualization—as “paragliders”—of their position in this multilevel structure. Third, we cluster these actors into groups of performance to better understand who is in a multilevel position to make progress with performance measurements over time. We use Ronald Burt’s representation of the combined effect of brokerage beyond group and closure within group to show that several of these performance groups do not follow his own principles very closely. Fourth, we provide evidence, for one of these groups, of the usefulness of combining constraint in the personal network of its members with constraint in their “extended” network—that is, for looking at the relationship between performance and borrowing from “dual alters” in the extended network. This shows that, when it is present, network lift from three-level structural wings is provided by different levels for different actors. Hypotheses induced by the paraglider metaphor can thus be tested progressively to provide new understandings of the structural conditions under which the Matthew effect of cumulative advantage operates. Finally, we list limitations of this three-level approach to the Matthew effect as examined here and suggest further developments for this approach.https://doi.org/10.1177/2059799115622764
collection DOAJ
language English
format Article
sources DOAJ
author Emmanuel Lazega
Marie-Thérèse Jourda
spellingShingle Emmanuel Lazega
Marie-Thérèse Jourda
The structural wings of Matthew effects: The contribution of three-level network data to the analysis of cumulative advantage
Methodological Innovations
author_facet Emmanuel Lazega
Marie-Thérèse Jourda
author_sort Emmanuel Lazega
title The structural wings of Matthew effects: The contribution of three-level network data to the analysis of cumulative advantage
title_short The structural wings of Matthew effects: The contribution of three-level network data to the analysis of cumulative advantage
title_full The structural wings of Matthew effects: The contribution of three-level network data to the analysis of cumulative advantage
title_fullStr The structural wings of Matthew effects: The contribution of three-level network data to the analysis of cumulative advantage
title_full_unstemmed The structural wings of Matthew effects: The contribution of three-level network data to the analysis of cumulative advantage
title_sort structural wings of matthew effects: the contribution of three-level network data to the analysis of cumulative advantage
publisher SAGE Publishing
series Methodological Innovations
issn 2059-7991
publishDate 2016-02-01
description The article presents a three-level network approach to the Matthew effect as a multilevel complement to Burt’s (2005) conception of the relationship between networks and performance. We first introduce a three-level dataset and the specificity of this data structure for explorations of cumulative advantage. Second, we present a population of scientists and provide a heuristic visualization—as “paragliders”—of their position in this multilevel structure. Third, we cluster these actors into groups of performance to better understand who is in a multilevel position to make progress with performance measurements over time. We use Ronald Burt’s representation of the combined effect of brokerage beyond group and closure within group to show that several of these performance groups do not follow his own principles very closely. Fourth, we provide evidence, for one of these groups, of the usefulness of combining constraint in the personal network of its members with constraint in their “extended” network—that is, for looking at the relationship between performance and borrowing from “dual alters” in the extended network. This shows that, when it is present, network lift from three-level structural wings is provided by different levels for different actors. Hypotheses induced by the paraglider metaphor can thus be tested progressively to provide new understandings of the structural conditions under which the Matthew effect of cumulative advantage operates. Finally, we list limitations of this three-level approach to the Matthew effect as examined here and suggest further developments for this approach.
url https://doi.org/10.1177/2059799115622764
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