Racial capitalism and STEM education in Chicago Public Schools

ABSTRACT

This article analyzes the role of STEM initiatives designed by city and corporate elites in a large urban district and outlines an alternative, grassroots vision for (STEM) education and city schools. Within a neoliberal context of gentrification, displacement, disinvestment, and privatization, STEM schools have become strategic components of Chicago’s ‘portfolio district’ that serve the interests of racial capitalism in three ways. First, STEM schools provide a claim to fairness in the midst of racist school closures. Second, STEM high schools are a corporate strategy for racially stratified labor force preparation that restricts curriculum and reifies tracking. Third, curriculum restriction prioritizes corporate interests over students’ capacity to shape their communities and the world. The authors draw on the wisdom of Chicago communities who have led resistance against corporate education reform to critique Chicago STEM policy and point to critical mathematics and science education as part of a model for sustainable community schools.     

Identification Properties of Recent Production Function Estimators

This paper examines some of the recent literature on the estimation of production functions. We focus on techniques suggested in two recent papers, Olley and Pakes (1996) and Levinsohn and Petrin (2003). While there are some solid and intuitive identification ideas in these papers, we argue that the techniques can suffer from functional dependence problems. We suggest an alternative approach that is based on the ideas in these papers, but does not suffer from the functional dependence problems and produces consistent estimates under alternative data generating processes for which the original procedures do not.     

How to Compete Against a Behavioral Newsvendor

We investigate newsvendor ordering behavior under competition. We present a laboratory experiment that documents the behavioral ordering regularities in competitive newsvendor environments, and an analytical model extending the standard theory of newsvendor competition by including an optimal best‐response policy for competing with a behaviorally biased newsvendor. We test the effectiveness of this policy using an out‐of‐sample experiment and find that it results in improved market share, service level and profitability.     

Efficiency or Competition? A Structural Econometric Analysis of Canada's AWS Auction and the Set‐Aside Provision

In 2008, Industry Canada auctioned 105 MHz of spectrum to a group of bidders that included incumbents and potential new entrants into the Canadian mobile phone market, raising $4.25 billion. In an effort to promote new entry, 40 MHz of spectrum was set‐aside for new entrants. In order to estimate the implicit cost of the set‐aside provision, we estimate the parameters of the bidders' profit function via a maximum match estimator based on the notion of pairwise stability in matches. We find that all telecommunications firms valued both geographic complementarities across auction licenses as well as absolute spectrum. Under a reasonable alternative scenario, our results indicate that the set‐aside led to a total profit loss of approximately 10%.     

Institutionalization or Decoupling? An Exploratory Analysis of the UN Global Compact LEAD Initiative

Institutionalization occurs when organizations adopt policies and practices in an attempt to increase their legitimacy and competitive position. This process assumes that an organization's formal policies (macro‐level) are translated into organizational practices (micro‐level). This translation, however, can fail to occur, resulting in organizational decoupling and de‐institutionalization. Drawing on an institutionalization typology based on different levels of legitimacy (macro) and taken‐for‐grantedness (micro), the article draws on data from an assessment of the United Nations Global Compact LEAD initiative, assessing the extent to which this initiative is being institutionalized in the member firms and examining the implications for the LEAD initiative and our thinking about institutionalization.     

Robust Bayesian model selection for variable clustering with the Gaussian graphical model

Statistics and Computing - Variable clustering is important for explanatory analysis. However, only few dedicated methods for variable clustering with the Gaussian graphical model have been...     

Network Embeddedness in Exploration and Exploitation of Joint R&D Projects: A Structural Approach

This paper analyses how network embeddedness affects the exploration and exploitation of R&D project performance. By developing joint projects, partners and projects are linked to one another and form a network that generates social capital. We examine how the location, which determines the access to information and knowledge within a network of relationships, affects the performance of projects. We consider this question in the setup of exploration and exploitation projects, using a database built from an EU framework. We find that each of the structural embeddedness dimensions (degree, betweenness and eigenvector centrality) have a different impact on the exploration and exploitation project performance. Our empirical analysis extends to project management literature and social capital theory, by including the effect that the acquisition of external knowledge has on the performance of the project.     

Nonparametric Estimation of the Number of Drug Users in Hong Kong Using Repeated Multiple Lists

We update a previous approach to the estimation of the size of an open population when there are multiple lists at each time point. Our motivation is 35 years of longitudinal data on the detection of drug users by the Central Registry of Drug Abuse in Hong Kong. We develop a two‐stage smoothing spline approach. This gives a flexible and easily implemented alternative to the previous method which was based on kernel smoothing. The new method retains the property of reducing the variability of the individual estimates at each time point. We evaluate the new method by means of a simulation study that includes an examination of the effects of variable selection. The new method is then applied to data collected by the Central Registry of Drug Abuse. The parameter estimates obtained are compared with the well known Jolly–Seber estimates based on single capture methods.     

Linear Increments with Non‐monotone Missing Data and Measurement Error

Linear increments (LI) are used to analyse repeated outcome data with missing values. Previously, two LI methods have been proposed, one allowing non‐monotone missingness but not independent measurement error and one allowing independent measurement error but only monotone missingness. In both, it was suggested that the expected increment could depend on current outcome. We show that LI can allow non‐monotone missingness and either independent measurement error of unknown variance or dependence of expected increment on current outcome but not both. A popular alternative to LI is a multivariate normal model ignoring the missingness pattern. This gives consistent estimation when data are normally distributed and missing at random (MAR). We clarify the relation between MAR and the assumptions of LI and show that for continuous outcomes multivariate normal estimators are also consistent under (non‐MAR and non‐normal) assumptions not much stronger than those of LI. Moreover, when missingness is non‐monotone, they are typically more efficient.