The ‘Bóias-Frias’:rural proletarization and urban marginality in Brazil

Book reviewed in this article: D'Incao e Mello, M. C. 1976: O ‘Bóia-Fria’ Singer, P. Martinez-Alier, V. 1975: As mulheres do caminhao de turma, Debate e Critica Stein, L. 1973: Gatos e ‘Bóias-Frias’ Gonzales, E. N. and Bastos, M. I. Gomes da Silva, J. and G. da Silva Rodrigues, V. L. Piazzolli, C. 1976: O ‘Bóia-Fria’-acumulaçào e miséria     

Spatial and Racial Patterning of Real Estate Broker Listings in New York City

It has been well documented that Black homeseekers face discrimination in the housing market in the form of racial steering and other institutional policies and practices that are critical in limiting housing access. Less is known about the mechanisms that operate on the other side of real estate transactions to perpetuate racially segregated neighborhoods. We investigated whether White and Black brokers face segregation in the housing market. That is, to what extent do White and Black brokers differentially market property listings in neighborhoods of varying racial composition? Using real estate listings extracted from the websites of two of the largest New York City real estate brokerages, we examined whether Black and White brokers market properties primarily in Black and White neighborhoods, respectively; and whether, controlling for gender and experience level, Black brokers had a lower average price per square foot than White brokers. Results showed that Black brokers overwhelmingly marketed properties in Black neighborhoods, with fewer listings in White areas. Black brokers also marketed properties with an average price per square foot that was $197 lower than White brokers. Black brokers who worked in offices in Black neighborhoods had the lowest asking price of all brokers. Taken together, Black and White real estate brokers control a bifurcated market in NYC, perpetuating residential segregation and Black–White income and wealth disparities.     

Our Collaborative Future: Activities and Roles of Stakeholders in Sustainability‐Oriented Innovation

While stakeholders have long been at the forefront of sustainable development debates, the emphases have tended to be on different stakeholder pressures, or managing stakeholder expectations about controversial issues. In this paper we bring a fresh direction to these debates and ask in what ways different stakeholders can contribute to sustainable innovation in firms. Based on 80 semi‐structured interviews, we conduct a fine‐grained qualitative analysis of stakeholder activities in sustainability‐oriented innovation (SOI) processes in 13 different companies across Europe. Our analysis identifies eight roles that stakeholders play in SOI processes: stimulator, initiator, broker/mediator, concept refiner, legitimator, educator, context enabler and impact extender. More traditional roles such as legitimator and educator are less common in our cases. However, emerging roles such as stimulator, concept refiner, context enabler and impact extender are clearly identifiable and could be particularly valuable for SOI. We enhance a collaborative perspective of stakeholder theory, finding that stakeholders can play highly collaborative and proactive roles, and argue that secondary stakeholders may actually be more relevant for SOI than primary stakeholders. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

Automated Induction of Rule-based Neural Networks from Databases

This paper describes our approach to the problem of automated knowledge acquisition from large databases of examples using an information-theoretic approach. Our previous research has resulted in practical algorithms (ITRULE) for the automatic induction of rules from large example databases. Utilizing these algorithms, the raw data can be transformed into a set of human readable IF THEN rules, thus giving insight into the knowledge hidden within the data. These rules can then be automatically loaded into an expert system shell. Alternatively, they can be used to build a new type of parallel inference system—a rule-based neural network. This process enables a prototype expert system to be automatically generated and up and running in a matter of minutes, compared with months using a manual knowledge-acquisition approach. The resulting expert system can then be used as a sophisticated search and analysis tool to query the original database capable of reasoning with uncertain and incomplete data.     

Dwelling Age Heteroskedasticity in Repeat Sales House Price Equations

Several authors have attributed the heteroskedasticity observed in repeat sales house price equations to the length of time between sales. Recently, Goodman and Thibodeau (1995) developed a theoretical model that relates heteroskedasticity in hedonic house price equations to dwelling age. Using data for nearly 2,000 repeat sales in Dallas, Texas, this research examines whether repeat sales heteroskedasticity is related to dwelling age, to the length of time between sales, or to both. An iterative generalized least squares procedure that explicitly models the residual variance is used to obtain robust parameter estimates and to increase the efficiency of the usual repeat sales price indices.