What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

Sampson, Robert J. 2012. Great American city: Chicago and the enduring neighborhood effect. Chicago: University of Chicago Press. ISBN-13: 9780226734569. pp. 552, $27.50 cloth. Robert J. Sampson’s ...

Great American city: Chicago and the enduring neighborhood effect

To Dwell Among Friends: Personal Networks in Town and City.

Black Picket Fences: Privilege and Peril Among the Black Middle Class. Mary Patillo-McCoy. Chicago, 1L, and London, UK: The University of Chicago Press, 1999. xii. 276pp. (Cloth US$25.00; PaperUSS15.00)

Black Picket Fences: Privilege and Peril Among the Black Middle Class

We propose a theoretically and practically improved density-based, hierarchical clustering method, providing a clustering hierarchy from which a simplified tree of significant clusters can be constructed. For obtaining a “flat” partition consisting of only the most significant clusters (possibly corresponding to different density thresholds), we propose a novel cluster stability measure, formalize the problem of maximizing the overall stability of selected clusters, and formulate an algorithm that computes an optimal solution to this problem. We demonstrate that our approach outperforms the current, state-of-the-art, density-based clustering methods on a wide variety of real world data.

Density-based clustering based on hierarchical density estimates

The social integration of a city depends on the extent to which people from different neighborhoods have the opportunity to interact with one another, but most prior work has not developed formal w...

The Social Integration of American Cities: Network Measures of Connectedness Based on Everyday Mobility Across Neighborhoods:

This article develops and assesses the concept of triple neighborhood disadvantage. We argue that a neighborhood’s well-being depends not only on its own socioeconomic conditions but also on the co...

https://journals.sagepub.com/doi/pdf/10.1177/0003122420972323

Triple Disadvantage: Neighborhood Networks of Everyday Urban Mobility and Violence in U.S. Cities:

When love meets hate: The relationship between state policies on gay and lesbian rights and hate crime incidence

This study estimates the effect of neighborhood disadvantage on bachelor’s degree attainment with data from a long-term follow-up of the Project on Human Development in Chicago Neighborhoods. We fo...

The Varying Effects of Neighborhood Disadvantage on College Graduation: Moderating and Mediating Mechanisms:

Race and class disparities in COVID-19 cases are well documented, but pathways of possible transmission by neighborhood inequality are not. This study uses administrative data on COVID-19 cases for roughly 2000 census tracts in Wisconsin, Seattle/King County, and San Francisco to analyze how neighborhood socioeconomic (dis)advantage predicts cumulative caseloads through February 2021. Unlike past research, we measure a neighborhood’s disadvantage level using both its residents’ demographics and the demographics of neighborhoods its residents visit and are visited by, leveraging daily mobility data from 45 million mobile devices. In all three jurisdictions, we find sizable disparities in COVID-19 caseloads. Disadvantage in a neighborhood’s mobility network has greater impact than its residents’ socioeconomic characteristics. We also find disparities by neighborhood racial/ethnic composition, which can be explained, in part, by residential and mobility-based disadvantage. Neighborhood conditions measured before a pandemic offer substantial predictive power for subsequent incidence, with mobility-based disadvantage playing an important role.

https://www.science.org/doi/pdf/10.1126/sciadv.abl3825?download=true

Brian L. Levy

Papers

The Social Integration of American Cities: Network Measures of Connectedness Based on Everyday Mobility Across Neighborhoods:

Triple Disadvantage: Neighborhood Networks of Everyday Urban Mobility and Violence in U.S. Cities:

When love meets hate: The relationship between state policies on gay and lesbian rights and hate crime incidence

The Varying Effects of Neighborhood Disadvantage on College Graduation: Moderating and Mediating Mechanisms:

Neighborhood socioeconomic inequality based on everyday mobility predicts COVID-19 infection in San Francisco, Seattle, and Wisconsin