Achievements and Downfalls of Housing and Subsequent Data Visualization Reflected in Chapter 8, “Tenant Transitions”

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Chapter 8 in Climbing Mount Laurel addresses the potential long-term effects that a housing development like the Ethel Lawrence Homes [ELH] could have on the population that lives in them.  On a whole, Massey et al. conjectured that the lives of the residents have “significant[ly] improved” since the move compared to those of non-residents (145). Some of the criteria that the researchers used to measure this ‘improvement’ were having better schools, less “school disorder and violence,” more “quiet place[s] to study” for youths, more “supportive parental behavior,” and more hours spent studying by school-aged children (182). Whether grades improved for the children who reside in ELH has been disputed seeing as the G.P.A data was not only self reported and therefore not totally scientific but also potentially statistically insignificant because the previously attended schools attended were, on a whole, worse than those in Mount Laurel.

Massey et al. presents this data with both written explanation and visual graphs.  The social scientists carefully lay out tables, flow charts, bar charts, and figures with hypothetical future statistics to supplement written data.  While this graphical representation is beneficial for visualizing trends – sometimes words are hard to conceptualize – there remains a major gap in comprehension. Nominally, the conclusions drawn are hard to understand as a statistical analysis layman. Despite Massey et al.’s brief explanation, someone with a limited background in statistics or data analysis cannot readily understand what “p” means, what the index “points” referred to are, exactly how the scientists hypothesized and calculated the long-term effects of the move, what the “z-scores” are, etc.  In this regard, chapter 8 is best read and understood by an erudite person familiar with social science data analysis. That said, it is unclear whether a more interactive data visualization, perhaps one on a computer and therefore less static, would be beneficial to laymen considering the fact that the lack of comprehension stems not from the conclusions themselves, but rather how the analysis was conducted.

Tangentially, considering the hypothetical long-term conclusions, it seems that the residents of ELH will, on a whole, achieve higher levels of success and have “new” trajectories that they would not otherwise have had access to had they not been residents (181).  However, while this trend is generally positive, it should not be forgotten that the population of ELH is small and that this positive change in economic and social opportunity exists on a microscopic and place-by-place scale.  Rather than ubiquitously altering the way that economic, social, educational, and geographical stratification happens with regard to race and class, the ELH model only gives opportunities to a very small populations, specifically, those deemed “good tenants” (195). Even if this type of development were replicated in other communities, it would still only affect a few, carefully selected persons. In other words, ELH’s positive change lacks systemic significance.