9512	Assessment Initial Draft	Final Draft comments
Abstract	No abstract in this draft, but it should be easy to extract from the existing research question section.	The abstract is well done.
Research Question	The general research aims seem pretty clear, although the specific statements are sometimes awkward or ambiguous.  For example, the most focused statement of the research question suggests that the project will look at the relationship between changing neighborhood composition and student achievement - this was probably meant to be changes in student achievement.  All this means is that it will benefit from further editing for clarity and typographical errors. Note that "math" was left out of the sentence giving the final, formal statement of the research question.	Clearly stated.  Research question is clearly-worded and appropriately-placed in the proposal.
Literature Review	The literature review is in good shape, well organized with good coverage.  It also will benefit from a bit of close editing (particularly to ensure that the causes and effects being discussed are always clear), and the very first sentence should be omitted.	Substantively unchanged (good organization and breadth of literature).
Data & Analysis	The data seem okay for the project.  Assuming the data are available, the research might benefit from using the 2011-12 academic year as well.  With this data added, then the same cohort that were in the 3rd grade in one round are in the 8th grade in the next round.  Then, any compositional changes within the cohorts would be evident (while comparisons of different cohorts in different periods combine changes over time within cohorts and differences across cohorts).  (For example, economic cycles could alter the proportion of a cohort who qualify for free lunch.)  This is not essential, rather an opportunity to consider.  Moreover, using more than two points in time provides significantly more leverage for arguing that changes in dependent variables are due to independent variables. It might be worth some effort to see if anyone has done a useful mapping between census boundaries and school district boundaries or neighborhoods, for previous research, that the project could simply adopt for attaching census data to the school neighborhoods.  Otherwise this can be time consuming.  It is not clear from the presentation if the data on student performance are available at the individual level (which potentially would let you assess changes in the performance of students relative to their neighborhood conditions).  If individual level data are available, it is not clear why the research design would focus the research on aggregates of students performance.  Regardless of the answer to the previous point, it might help to think through what ideal data would look like to solve the project goals.  This might involve: individual level data on students' performance and their families' circumstances followed over time, plus aggregated data on schools and neighborhoods over time.  Such data would then allow for an analysis that compares students' performances over time, looking simultaneously at the influence of parents income, neighborhood economic status, quality of students in relevant school, and other characteristics of relevant schools.  This would allow quality of neighborhoods, schools, and family circumstances all to vary, including variation independent of the family (neighborhood change) and due to family "choice" (relocating to a new neighborhood).  Thinking through how such "ideal" data would permit isolating the competing causes, showing how each of the shortcomings of the data actually available reduce what the research can hope to discover.	The data and the data analysis plans appear on their way to good plan, but the presentation leaves us problematically uncertain about important aspects.  You have informally suggested that the individual level data is not public but available to you through your position - this is not discussed in the proposal (and recall that this probably implies the data you intend to you requires a human subjects review).  The content of the student level data set is not specified in the proposal, nor is it evident if the data include student identifiers that permit connecting students' records (specifically, test scores) across years.  The proposal provides no insight about the proposed gentrification variable that is crucial to the project; we do not know what it represents beyond the general idea.   To the degree that alternative data sources exist, it is better to say that some considerations such as derivative effects of gentrification are beyond the scope of this study or something similar, rather than that they are not covered in the datasets being used.  If data are readily available (e.g., crime data), then one needs to supply a more sensible reason for excluding something that appears analytically appropriate than simply saying it does not happen to be in the data set at hand.  A researcher, however, has the right to make a reasoned case for the scope of a project and that will be sufficient unless a reviewer believes that the validity or integrity of the project is undermined by the scope decisions. One suggestion (contrary to the scope limits):  It is probably worth the time to talk to people who do research on social issues using area data in NYC (such as Amanda and Patrick Sharkey in Sociology).  Some of what the proposal calls "derivative changes" in neighborhoods (and possibly in schools) may be readily available from other existing data sets.  Given the period for your study, it is unfortunately likely that no one has the appropriate data for the appropriate time.  Still, finding people likely to know and asking them requires a relatively low investment of time and effort compared to the value the data could have for you.  (Of course, you don't want to make the research plan too complex, but finding such data does not determine the order in which you investigate this issue.  It does, however, give you the freedom to change that order to what best serves your long-term goals).
Causal Interpretations	The basic causal idea is clear, but the mechanisms could use further development, particularly because this is decisive for the research design.  If we look at possible mechanisms - for example, simple compositional changes in the student body (more or fewer students from high performance families), derivative changes in the neighborhood (e.g., exposure to violence or books), or derivative changes in the school atmosphere (e.g., shifts in the status implications of school performance or associating with alienated cliques) - we have different things to look for in the data. Also, relative to the underlying motivation for this research, consider the reality that the school neighborhoods in NYC are to some degree a zero sum game (they are not to the degree that NYC experiences changes through population exchanges with other areas, particularly surrounding ones, or through changes in the NYC economic conditions).  So, to the degree we are shifting families' locations among a fixed set of neighborhoods, a rise in the average income in some implies a decline in others.  This means that the economic diversity argument somewhat relies on the assumption that returns to diversity decline at some point of economic improvement.  Or, to put it differently, the difference in educational outcomes between poor and moderate income neighborhoods is considerably greater than the difference between moderate and high income neighborhoods.  If this is not true, then high income people have a strong interest in sustaining neighborhoods of concentrated affluence.  And the diversity argument becomes one of advocating for the egalitarianism of mediocrity.  Those of us favoring egalitarian policies may find this unappealing to consider, but we would be analytically incompetent not to recognize the issues. Also, what are the implications of people's capacities to exercise choice over the schools their children attend in New York City?  Presumably this is less of an issue (for research) at lower grades, but this possible issue should be addressed if only to show that it is not a problem.  That is to say, how much does school choice potentially attenuate the effects of residential realignments on changes in the student composition of schools?  Is the research design able to distinguish the changes in neighborhood residential composition from changes in student body composition if there is potential variation in this relationship?  And if this variation is possible, what does it imply about the causal expectations?	The causal analysis in the final draft of the proposal is significantly improved, particularly in the recognition that associations between gentrifying neighborhoods and changing student achievement can be driven by multiple causes,  potential including selection effects. Still, some issues (including some mentioned in the feedback on the previous version) have not been addressed adequately.   The limitations we see in the discussions of the data and analytic strategies appear to reflect this limitation.  The goal of this project is to measure a possible causal effect, a change in the quality of learning through public schools due to gentrification processes.  The only way the analytic strategy is likely to become successful, is by taking into account the critical causal possibilities.
Research Contribution	The effort to explain the potential value of the project would be much stronger if it started by stressing what it can add to the existing scholarly literature.  However much the information is relevant to policy, it is only a valuable contribution because it discovers things not already known in the scholarship.	The proposal clearly and effectively articulates the theoretical and practical value of the project.
Citations & Bibliography	The reference structure seems fine, except that some of the bibliographic entries appear incomplete.	Well done.
Quality of Writing & Organization	The writing is fine.  A thorough editing would be beneficial.	Well written.
Priorities for Revising / Responsiveness to Feedback	The priorities would seem to include clarifying the causal analysis, refining the research question, and clarifying what exists in the data and how it will be used, all in relationship to each other.	This version of the proposal is well revised and addresses much of the feedback effectively.
Miscellaneous Notes
Proposal		While a few issues still call out for attention, the proposal as a whole aims at a well-conceived project with appropriate data.
Class Overall		A good job in all aspects of the course.