Data-Driven Approach to Understanding Complex Urban Phenomena: A Preliminary Study on the Gentrification of H Street NE in Washington, DC

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

- The Introduction should explain more clearly, what the objective of the article is, what research question(s) it is trying to answer, or what specific hypothesis it is trying to test in this research.

- The authors attempt to test a complex theory with overly simple data –which, moreover, are not for exactly the same years. Moreover, the business data are from two years too far apart (2003 and 20216) and the research would have benefited from adding data from intermediate years to see how the gentrification is progressing. Nevertheless, this is acceptable as a preliminary study.

- In the case of Figure 2, I propose to replace it with a table including the differences for each category (businesses of each type in 2016 minus businesses of the same type in 2013). However, if you prefer to keep the graph, I suggest ordering the types of business from the biggest to the smallest difference between 2003 and 2016. The aim is to make the changes in business types more clearly visible.

- The authors argue that gentrification in H Street NE was due to the death of former residents, not relocation. In other words, replacement instead of displacement. Nevertheless, I think that to verify this theory, demographic data (such as the change in the population pyramids showing the variation in the sex and age structure) as well as data on housing tenure is lacking: is the neighbourhood dominated by home ownership or rental housing? If the latter were true, there could have been rent increases in 2006-2007 that could have forced residents to migrate. The authors should take into account alternative arguments that could go against their explanation.

- Conclusions are too brief; they should answer the starting hypotheses or specific objectives (which do not exist in the Introduction). The authors should also elaborate on future research improvements that could mitigate the problems found in this preliminary study.

Author Response

Comment 1: The Introduction should explain more clearly, what the objective of the article is, what research question(s) it is trying to answer, or what specific hypothesis it is trying to test in this research.

Response 1: We thank Reviewer 1 for this comment. In the revised manuscript, we have added a new subsection 2.3 in which we explain what we perceive the main knowledge gap on gentrification to be, and what we hope to accomplish by taking an approach informed by complex systems theory.

Comment 2: The authors attempt to test a complex theory with overly simple data –which, moreover, are not for exactly the same years. Moreover, the business data are from two years too far apart (2003 and 20216) and the research would have benefited from adding data from intermediate years to see how the gentrification is progressing. Nevertheless, this is acceptable as a preliminary study.

Response 2: We thank Reviewer 1 for this comment. We have now expanded our data sets to cover all five areas (demographics, income, home prices and rent, commercial activities, and social cultural activities) we expect to find signatures of gentrification. We now have longitudinal data from 2010 to 2019 on five census tracts making up H Street NE, in addition to demographics data from the census of 2000. These data sets cover not only demographics, but also income and rent, to supplement home sales and home price data from 1993 to 2019. Finally, we also collected historical business registrations in each of the years between 2003 and 2019, allowing us to identify the sudden doubling of restaurants and nonclassified businesses in 2013 and 2012 respectively.

Comment 3: In the case of Figure 2, I propose to replace it with a table including the differences for each category (businesses of each type in 2016 minus businesses of the same type in 2013). However, if you prefer to keep the graph, I suggest ordering the types of business from the biggest to the smallest difference between 2003 and 2016. The aim is to make the changes in business types more clearly visible.

Response 3: As suggested by Reviewer 1, we have replaced Figure 2 in the original manuscript by Table 2, in which we list the numbers of registered entities for five slowly declining business types and two business types experiencing sudden changes over the years 2003 to 2019. This has indeed make the changes in business types more clearly visible.

Comment 4: The authors argue that gentrification in H Street NE was due to the death of former residents, not relocation. In other words, replacement instead of displacement. Nevertheless, I think that to verify this theory, demographic data (such as the change in the population pyramids showing the variation in the sex and age structure) as well as data on housing tenure is lacking: is the neighbourhood dominated by home ownership or rental housing? If the latter were true, there could have been rent increases in 2006-2007 that could have forced residents to migrate. The authors should take into account alternative arguments that could go against their explanation.

Response 4: We thank Reviewer 1 for this comment. We have since realised that old residents dying and them moving out (or any combination of the two) can produce the same demographic changes. In fact, with the more comprehensive data sets acquired for the revision, we realised that the gentrification of H Street NE had progressed in three waves, with the first starting before 2000, the second starting around 2000, and the third starting shortly before 2010. From the demographics data, we can see extensive racial displacements in the first wave of gentrification could easily explain the church closures of 2006/2007. From the population pyramids and income data of the areas affected by the first wave of gentrification, we could also see the poor old Black residents who has been living there for a long time being replaced by rich new White residents who were predominantly middle-aged at the start of the gentrification, and thereafter slowly ageing in place. In these areas that gentrified early, the renters proportion and rent levels have remained more or less constant over the years. In both areas affected by the second wave of gentrification, the rich new White residents have not yet fully established themselves (missing juvenile sub-distribution, and little ageing in place). In one of the areas affected by the second wave of gentrification, the proportion of homeowners and the rent level started increasing sharply since 2013. In this second area, the racial displacement indeed progressed faster than elsewhere along H Street NE. In view of these new findings, we have revised our narrative on the gentrification of H Street NE.

Comment 5: Conclusions are too brief; they should answer the starting hypotheses or specific objectives (which do not exist in the Introduction). The authors should also elaborate on future research improvements that could mitigate the problems found in this preliminary study.

Response 5: We thank Reviewer 1 for this comment. We have since expanded our conclusions to incorporate our new findings. We explain the new set of problems we now face in the light of these new findings, and discuss what further research could be done to address these problems at the end of the Discussion section.

Reviewer 2 Report

Comments and Suggestions for Authors

In their manuscript, the authors provide a preliminary study on the gentrification of H Street NE in Washington DC, USA based on three indicators including monthly home sales, business registration data, and church registration. The findings of the paper highlight a new justification for the gentrification of the  Street NE in Washington DC, USA, which is believed by the authors to be the true story. The manuscript should be reconsidered for a major revision. 

1) It is recommended to rephrase/restructure the current introduction where the ideas should ultimately narrow down to reflect the main knowledge gap tackled by the study. 

2) The introduction should clearly highlight the main goal of the study as well as the associated objectives (i.e., 3 objectives)

3) The paper lacks a literature review to explore previous gentrification-related studies and highlight the main knowledge gaps that this paper fills. 

5) Line 146, please change "Case Study of H Street NE, Washington DC, USA" into "Materials and Method"

4) Between lines 146 and 147, adding a figure to summarize the research methodology is recommended.

5)  Lines 196-198 "we expect to see changes in five data types: (1) demographics; (2) income; (3) home sales, home price, and rent; (4) commercial activities; and (5) social and 197 cultural activities." Please clarify the criterion for selecting these 5 gentrification-related indicators, while the literature on gentrification highlights other important indicators. 

6) Lines 198-203 "In the first data type (demographics), as the old residents were mostly 198 Blacks, while the new residents were Whites and Hispanics. If the new residents hold 199 better jobs, the gentrification will also appear in wealth and income data (the second data 200 type). Unfortunately, we did not manage to get any of the above data. " It is recommended to discuss this the "Discussion" section. 

7) Please enhance the quality of the Figures (e.g., Figure 1 and Figure 2) in the paper. 

8) The current methodology should be greatly improved, where currently it is based on comparing a few datasets (i.e., 3 potential gentrification indicators) between two periods (e.g., before gentrification and gentrification) and then highlighting findings based on assumptions and chronological order. Rather these findings should be based on strong evidence (i.e., interviews with stakeholders, urban planners, policymakers, and community groups that reinforce the authors' assumptions ).

9) In the discussion section, it is recommended to clarify the main contribution of this study and its uniqueness compared to existing/previous studies.

 10) The conclusion should highlight the research limitations and future research agenda. 

11) Overall, It is highly recommended to improve the flow of ideas as well as the connection between different sentences throughout the entire manuscript.

Author Response

Comment 1: In their manuscript, the authors provide a preliminary study on the gentrification of H Street NE in Washington DC, USA based on three indicators including monthly home sales, business registration data, and church registration. The findings of the paper highlight a new justification for the gentrification of the  Street NE in Washington DC, USA, which is believed by the authors to be the true story. The manuscript should be reconsidered for a major revision. 

Response 1: We thank Reviewer 2 for the chance to revise our manuscript. As it turned out, through the analysis of more data sets, the narrative behind the gentrification of H Street NE has changed, but become richer. Details are given in the revised manuscript.

Comment 2: It is recommended to rephrase/restructure the current introduction where the ideas should ultimately narrow down to reflect the main knowledge gap tackled by the study. 

Response 2: We thank Reviewer 2 for the suggestion. We have now added a subsection 2.3 to our revised manuscript, where we explain the knowledge gap behind existing studies of gentrification, and how an approach based on complex systems theory can better address this gap.

Comment 3: The introduction should clearly highlight the main goal of the study as well as the associated objectives (i.e., 3 objectives).

Response 3: This is done in Section 2.3.

Comment 4: The paper lacks a literature review to explore previous gentrification-related studies and highlight the main knowledge gaps that this paper fills. 

Response 4: In response to this comment by Reviewer 2, we have now moved the literature survey on gentrification in Washington DC to Section 2, and make this Section 2.1. The original literature survey on complex systems is now Section 2.2. We hope this arrangement, followed by Section 2.3 on the knowledge gap and complex systems approach, will be able to satisfy Reviewer 2.

Comment 5: Line 146, please change "Case Study of H Street NE, Washington DC, USA" into "Materials and Method".

Response 5: We thank Reviewer 2 for this suggestion. This has now been done.

Comment 6: Between lines 146 and 147, adding a figure to summarize the research methodology is recommended.

Response 6: We apologise that this has not been done, as we were not able to imagine what such a figure would look like. With additional data sets analysed for the manuscript, we tried to explain the logic behind the sequence of the analyses, and what features to look out for based on the theory of complex systems.

Comment 7: Lines 196-198 "we expect to see changes in five data types: (1) demographics; (2) income; (3) home sales, home price, and rent; (4) commercial activities; and (5) social and 197 cultural activities." Please clarify the criterion for selecting these 5 gentrification-related indicators, while the literature on gentrification highlights other important indicators. 

Response 7: We thank Reviewer 2 for this comment. We would like to point out these five data types cover nearly all aspects of change associated with gentrification. In fact, for each data type, we examine more than one variable to understand the nature of the change. We describe this systematically in Section 3.2. However, we also understand that the data sets we analyse are aggregated. Therefore, we are not able to ascertain whether the economic, cultural, and social effects of gentrification are positive or negative to a given household of old residents, how many old households experienced gentrification positively, and how many experienced it negatively. At the end of our Discussion section, we explained that such information can only be obtained through interviews, focus groups, or surveys of the various stakeholders, and that unfortunately, these require time and resources beyond what we currently have.

Comment 8: Lines 198-203 "In the first data type (demographics), as the old residents were mostly 198 Blacks, while the new residents were Whites and Hispanics. If the new residents hold 199 better jobs, the gentrification will also appear in wealth and income data (the second data 200 type). Unfortunately, we did not manage to get any of the above data. " It is recommended to discuss this the "Discussion" section. 

Response 8: We thank Reviewer 2 for this comment. We have since acquired high-resolution (in time, space, and ethnicity) demographics and income data that allowed us to track the racial displacement of poorer Blacks by richer Whites. We hope Reviewer 2 would find our findings interesting.

Comment 9: Please enhance the quality of the Figures (e.g., Figure 1 and Figure 2) in the paper. 

Response 9: We thank Reviewer 2 for this suggestion. Following the suggestion by Reviewer 1, we have replaced Figure 2 of the commercial landscape by a table showing selected business types over the years from 2003 to 2019. Figure 1 in the original manuscript is now Figure 4 in the revised manuscript. We suspect that Reviewer 2 objects to the noise in the data shown in the old Figure 1 (new Figure 4). Unfortunately, there is nothing we can do about this, as between 1993 and 2024, there were only 239 transactions over the 105 residential units along H Street NE. We would like to assure Reviewer 2 that the spike in 2016 (as well as the spike in 2001 after we used the correct data set) is statistically significant, even though we have not performed any test.

Comment 10: The current methodology should be greatly improved, where currently it is based on comparing a few datasets (i.e., 3 potential gentrification indicators) between two periods (e.g., before gentrification and gentrification) and then highlighting findings based on assumptions and chronological order. Rather these findings should be based on strong evidence (i.e., interviews with stakeholders, urban planners, policymakers, and community groups that reinforce the authors' assumptions ).

Response 10: We thank Reviewer 2 for this comment, which comes in two parts. In response to the first part of this comment, we have acquired many more high-resolution and longitudinal data sets. We hope Reviewer 2 would find the results of our analyses more compelling than those in the original manuscript. In the second part of this comment, Reviewer 2 suggested we interview various stakeholders. In the Discussion section, we explained how soft data collected directly from the stakeholders would be important for validating narratives generated from the hard aggregate data. However, we also explained our lack of time and resources to carry out these interviews. While revising our manuscript, we toyed with the idea of using existing oral histories curated by the Washington DC Library, to see if they touched on the gentrification of H Street NE. Unfortunately, because these oral histories were not collected with a study on gentrification in mind, interviewees talked about random topics in general. Since this oral history corpus is not extensively indexed, it is very difficult to do a search on it and in the end we gave up.

Comment 11: In the discussion section, it is recommended to clarify the main contribution of this study and its uniqueness compared to existing/previous studies.

Response 11: We thank Reviewer 2 for this comment. Instead of the Discussion section, we added the sentence "Through such a complex systems-inspired approach, we have answered some questions on the gentrification of H Street NE, but raised many more questions on the gentrification over the broader Washington DC area" to the end of the Conclusions section.

Comment 12: The conclusion should highlight the research limitations and future research agenda. 

Response 12: We thank Reviewer 2 for this suggestion. We have done so in the Discussion section instead.

Comment 13: Overall, It is highly recommended to improve the flow of ideas as well as the connection between different sentences throughout the entire manuscript.

Response 13: We thank Reviewer 2 for this suggestion. We have extensively rewritten and re-organized the manuscript. We hope Reviewer 2 would find the flow of ideas clearer in the revised manuscript.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors examine the gentrification of H Street NE in Washington, D.C., from the perspective of complex systems theory based on real-world data. This approach is, in my opinion, very promising and valuable.

The title very accurately describes these as preliminary studies. The outlined perspective of the theory of complex systems - with its quantitative methods - is not reflected in the research on this particular gentrification – based on three sets of data there are presented only qualitative arguments (no formulas are present in the text). Moreover, in many places the authors indicate that they cannot verify their (qualitative) assumptions because they do not have - for one reason or another - the appropriate data.

Therefore, even if I really like the idea of ​​research and using the methods of the theory of complex systems, the implementation of this idea uses the previously outlined perspective to a very limited extent, essentially not going beyond heuristics.

Moreover, it seems to me that invoking the theory of complex systems is not necessary for the reasoning presented by the authors. The use of these concepts is allegorical at best.

In addition, the presentation of concepts related to complex systems (Chapters 1 and 2) seems rather general and not very understandable to me. For example: giving the value of the beta exponent (line 100) without its definition makes no sense. Also, the statement that "regular systems (...) can be accurately described using simple mathematics" is simply untrue and in my opinion shows a superficial understanding of the subject (unnecessarily mentioned in the text).

I eagerly await the development of complex systems theory methods for studying urbanization processes. I like the idea of ​​the article's research very much. However, I have doubts whether the presented reasoning constitutes sufficient material for publication.

Author Response

Comment 1: The authors examine the gentrification of H Street NE in Washington, D.C., from the perspective of complex systems theory based on real-world data. This approach is, in my opinion, very promising and valuable.

Response 1: We thank Reviewer 3 for these positive comments.

Comment 2: The title very accurately describes these as preliminary studies. The outlined perspective of the theory of complex systems - with its quantitative methods - is not reflected in the research on this particular gentrification – based on three sets of data there are presented only qualitative arguments (no formulas are present in the text). Moreover, in many places the authors indicate that they cannot verify their (qualitative) assumptions because they do not have - for one reason or another - the appropriate data.

Response 2: We thank Reviewer 3 for this comment. All four reviewers pointed out the critical weakness of using only three data sets, one of them consisting of snapshots in 2003 and 2016, in the original manuscript. In our revision process, we have acquired many more high-resolution and longitudinal data sets that allowed us to illustrate the power of a complex systems approach to studying the gentrification phenomenon where, as far as possible, we use the different data sets to cross verify features found in other data sets.

Comment 3: Therefore, even if I really like the idea of ​​research and using the methods of the theory of complex systems, the implementation of this idea uses the previously outlined perspective to a very limited extent, essentially not going beyond heuristics.

Response 3: We thank Reviewer 3 for this criticism, and hope that Reviewer 3 agrees with us that we have now gone beyond heuristics in our analyses of the greatly expanded data sets, guided by our understanding of the theory of complex systems. In all honesty, the narrative created by chaining up cascading events chronologically is a qualitative first step. But this first step would later allow us to quantitatively test for causation, by checking which sub-sequences of events appear more frequently than expected in a systematic study of a large number of gentrified or gentrifying neighbourhoods.

Comment 4: Moreover, it seems to me that invoking the theory of complex systems is not necessary for the reasoning presented by the authors. The use of these concepts is allegorical at best.

Response 4: We are sorry to hear Reviewer 3 feeling this way about our use and presentation of complex systems theory. We have added an additional paragraph on complex systems in Section 3.2, to better explain why and how we analyse the data sets on demographics, income, home prices and rent, commercial activities, and social activities. We hope this will make it clear to Reviewer 3 why our analyses and the construction of a narrative must be guided by the theory of complex systems.

Comment 5: In addition, the presentation of concepts related to complex systems (Chapters 1 and 2) seems rather general and not very understandable to me. For example: giving the value of the beta exponent (line 100) without its definition makes no sense. Also, the statement that "regular systems (...) can be accurately described using simple mathematics" is simply untrue and in my opinion shows a superficial understanding of the subject (unnecessarily mentioned in the text).

Response 5: We apologise to Reviewer 3 for the confusing presentations on complex systems. We have rewritten the paragraph on urban scaling to hopefully make it clearer. In our rush to finish the revision, we made no further clarifications to the other complex system concepts. If the reviewers are not worry about the eventual length of the paper, we can prepare figures that can help illustrate these concepts.

Comment 6: I eagerly await the development of complex systems theory methods for studying urbanization processes. I like the idea of ​​the article's research very much. However, I have doubts whether the presented reasoning constitutes sufficient material for publication.

Response 6: We understand Reviewer 3's reservations on the original manuscript, and hope that the revised manuscript with the analyses and cross validations between many more data sets will remove this doubt.

Reviewer 4 Report

Comments and Suggestions for Authors

The author, through long-term observation of H Street NE in Washington DC, has discovered a phenomenon distinct from traditional gentrification, thereby enriching the research on gentrification. I believe the research question is innovative and holds significant research value. The research methods and overall structure of the paper are reasonable and adequately support the conclusions.

However, it must be noted that despite the author's efforts to compensate for data gaps in the discussion, these gaps still impact the conclusions of the paper. For instance, it is difficult to observe the demographic, social, and economic changes that occurred on H Street NE in Washington DC over the decade-long study period. These changes are crucial for understanding and revealing the processes and mechanisms of gentrification.

Despite some shortcomings, I believe the paper has clearly explained the gentrification phenomenon of H Street NE in Washington DC, as mentioned in the title. This paper serves as a preliminary study of gentrification on H Street NE in Washington DC. If the author can incorporate analyses from alternative data sources such as remote sensing data, Twitter data, and electricity usage data to provide a more detailed observation and revelation of the gentrification phenomenon in this area, it would be highly anticipated.

Author Response

Comment 1: The author, through long-term observation of H Street NE in Washington DC, has discovered a phenomenon distinct from traditional gentrification, thereby enriching the research on gentrification. I believe the research question is innovative and holds significant research value. The research methods and overall structure of the paper are reasonable and adequately support the conclusions.

Response 1: We thank Reviewer 4 for the positive remarks. Unfortunately, the narrative we arrived at in the original manuscript is mistaken because of the few data sets employed. With the many more, high-resolution, and longitudinal data sets acquired during our revision, we have a new and richer narrative.

Comment 2: However, it must be noted that despite the author's efforts to compensate for data gaps in the discussion, these gaps still impact the conclusions of the paper. For instance, it is difficult to observe the demographic, social, and economic changes that occurred on H Street NE in Washington DC over the decade-long study period. These changes are crucial for understanding and revealing the processes and mechanisms of gentrification.

Response 2: We thank Reviewer 4 for this comment. All four reviewers objected to the small number of data sets used, which resulted in gaps in our narrative. We have since acquired many more sets of high-resolution (in time, in space, and in ethnic compositions) longitudinal data. The analyses of these data sets required much more work, but allowed us to use one data set to cross validate features found in another data set. It is through these data sets and their analyses that we realised that there were three waves of gentrification across H Street NE, how the earliest first wave of gentrification that started before 2000 led to the church closures of 2006 and 2007, and how the second wave of gentrification that started shortly before 2010 created conditions for the numbers of restaurants and nonclassified businesses to double suddenly in 2013 and 2012. Unfortunately, some gaps remain in our new narrative, because our data sets do not allow us to time the start of the first wave of gentrification. In spite of this, we hope Reviewer 4 will find our revised manuscript more acceptable for publication than the original manuscript.

Comment 3: Despite some shortcomings, I believe the paper has clearly explained the gentrification phenomenon of H Street NE in Washington DC, as mentioned in the title. This paper serves as a preliminary study of gentrification on H Street NE in Washington DC. If the author can incorporate analyses from alternative data sources such as remote sensing data, Twitter data, and electricity usage data to provide a more detailed observation and revelation of the gentrification phenomenon in this area, it would be highly anticipated.

Response 3: We thank Reviewer 4 for suggesting the use of alternative data sets such as remote sensing data, Twitter data, and electricity usage data. These are proxies for the demographic, economic, and social dimensions of gentrification, and would be helpful additions to our data sets. Unfortunately, we do not know how to get such data at the scale of the H Street Corridor for these data to be useful.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you for taking into account all my comments on the first version of the article. I think the final version is much stronger and deserves to be published in Urban Science.

Reviewer 2 Report

Comments and Suggestions for Authors

I don't see this manuscript publishable in its current version where it lacks solid methodological soundness. Also, the quality of the content still needs enhancement. 

Author Response

Comment 1: I don't see this manuscript publishable in its current version where it lacks solid methodological soundness. Also, the quality of the content still needs enhancement. 

Response 1: We are sorry to see that Reviewer 2 remained unconvinced even though we have made substantial changes to the manuscript, with the addition of many important data sets. We leave the final decision to the editor.

Reviewer 3 Report

Comments and Suggestions for Authors

The article has been significantly improved, both enriched with data and the argumentation has been strengthened. The argumentation presented in this way is a contribution to the development of the application of the methods of the theory of complex systems to the sciences of urbanization processes.

I have two minor editorial notes.

I strongly suggest to improve the readability of Figures descriptions

In my opinion, the sentence in lines 814-816 is unnecessary - it can be deleted.

Author Response

Comments 1: The article has been significantly improved, both enriched with data and the argumentation has been strengthened. The argumentation presented in this way is a contribution to the development of the application of the methods of the theory of complex systems to the sciences of urbanization processes.

Response 1: We thank Reviewer 3 for the positive assessment on our revised manuscript.

Comments 2: I have two minor editorial notes.

Response 2: We have responded to the editorial notes as best as we can. In addition, after submitting the first revision, we obtained demographics data from the 1990 census, and realised that the gentrification of H Street NE started at the same time shortly after 2000, but progressed at different speeds in the five census tracts. We made changes to our narrative to incorporate this finding.

Comments 3: I strongly suggest to improve the readability of Figures descriptions

Response 3: We read through the captions of all figures, and feel that Reviewer 3 is probably referring only to Figures 1, 2, 3, and 6. We have expanded the captions of these figures, and also made sure that the caption of the newly added Figure 7 would meet Reviewer 3's expectations.

Comments 4: In my opinion, the sentence in lines 814-816 is unnecessary - it can be deleted.

Response 4: We do not know which lines Reviewer 3 is referring to, because lines 814-816 in the revised manuscript are within the list of references. If Reviewer 3 clarifies which sentences are inappropriate, we will be happy to delete them.

Round 3

Reviewer 3 Report

Comments and Suggestions for Authors

The redundant sentence is "Unfortunately, most members of this team are based in Asia and are thus unable to justify using additional resources to study a phenomenon so far away." at lines 722-724, p. 18, several lines before Section 5. Conclusions.