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Cited by 250

The DOI matches its OpenAlex record; 2 of the 2 references it cites were found in a registry or an index.

Evolution on a Dancing Landscape: Organizations and Networks in Dynamic Blau Space

J. M. McPherson, James Ranger‐Moore·1991·Social Forces

Abstract

This article develops and tests an evolutionary model of the growth, decline, and demographic dynamics of voluntary organizations. The model demonstrates a strong analogy between the adaptive landscape of Sewall Wright (1931) and the exploitation surfaces generated by a model of member selection and retention for voluntary associations. The article connects the processes of membership recruitment and loss to the social networks connecting individuals. The model generates dynamic hypotheses about the time path of organizations in sociodemographic dimensions. A key idea in this model is that membership selection processes at the individual level produce adaptation in communities of organizations. The article concludes with an empirical example and some discussion of the implications of the model for a variety of research literatures.

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OpenAlex · 10.1093/sf/70.1.19

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Metadata

Authors
McPherson, J. M., & Ranger‐Moore, J.
Venue
Social Forces
Publisher
Oxford University Press
Published
1991-09-01
Volume
70
Issue
1
Pages
19-19
ISSN
0037-7732 (ISSN-L)
OpenAlex
W2147433013
Cited by
250
References
2
FWCI
5.56
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Evolution on a Dancing Landscape: Organizations and Networks in Dynamic Blau Space. https://app.cochat.ai/papers/10.1093/sf/70.1.19
The paper
McPherson, J. M., & Ranger‐Moore, J. (1991). Evolution on a Dancing Landscape: Organizations and Networks in Dynamic Blau Space. Social Forces. https://doi.org/10.1093/sf/70.1.19

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.