Revise & Resubmit

EXAMPLE 1

I appreciate the hard work the author has put into their revised manuscript. I think the changes they have made have improved the paper. However, I still see some issues that in part remain from the original manuscript and could be addressed to ensure the validity of the results and strengthen the overall contributions of the paper. 

The approach for including transportation elements in the data seems somewhat problematic. From the text and the author’s comments, it seems that minor mentions of transportation terms might have been counted together with more developed platforms and policies. This concern arises from several aspects of the manuscript: 

First, transportation mode is identified as a theme. This could be a problem since the mention of a transport mode in itself does not seem sufficient for including that mention in the data. It is more about the context in which it is mentioned. This issue might be more relevant to mentions that come from “labels like the environment (12% of websites), community development (4% of websites), housing (3% of websites), or another topic.” There is obviously some grey area. A housing platform advocating for density along transit corridors might be identified as a transportation policy and this might be justifiable to some extent, even though the focus is on housing. But would a platform advocating for suburban development with an example of kids safely riding bikes be marked as a transportation policy? Both examples are problematic but the second one especially so. The author should consider giving examples of what counts as a transportation policy that is counted and what does not. If the data includes brief mentions of transport modes/topics that do not amount to a transportation policy, the author should consider removing them from the data. 

Second, the author uses (at least) three different terms to describe the transportation text that is included in the data: transportation platform, transportation policies, and transportation issues. The three are used interchange although their scope and depth are different. I recommend choosing the most appropriate term based on the data collection process (i.e. ‘issue’) and using it throughout the paper. Having said that, it might also be valuable to assess whether having more developed transportation platforms (and identifying solutions) lead to better electoral outcomes than merely mentioning transportation issues. 

Another limitation of the study is that the analysis does not account for the overall number of issues/platforms a candidate has. Maybe candidates with transportation platforms win more because they have more platforms on their website in general, which transportation is just one of, and not because of the transportation platform itself. In that case, the transportation platform is just a proxy for the scope and depth of the agenda that a candidate advances. This (and other comments) should at least be acknowledged as a limitation at the end of the paper. 

Page 14, lines 1-3: “This may indicate transportation is less salient in denser areas where transportation networks are more developed or more salient in areas with lower density that are more car-dependent with fewer mobility alternatives.” – I do not find this explanation convincing. Surely transportation issues are salient in dense localities, where there is more transit and congestion is a problem. It might be that the variable for population size is also capturing some of the effect related to density. Even if multicollinearity is low, the two might be related in a way that affects model results (more populated localities are typically also denser). What happens if you run the model without population size? Alternatively, could the log transformation be affecting the model outcomes? 

Page 19, lines 3-4: “Democrat affiliation was associated with local electoral performance, with Democrat candidates winning percentage almost four times higher than Republican candidates.” – This might be related to the sampling strategy and the final sample, which includes more candidates from California or cities in general. The author should be careful with generalizing to broader contexts given the data collection approach. 

Page 7, lines 16-19: “Using Ballotpedia to identify local general elections in 2022, I pooled 548 candidates from local elections in eight states and the District of Columbia.” – The author should list all eight states. I am not sure they are all explicitly mentioned in the text. 

In response to R3Q3, the author noted that they added text explaining that data were collected in 2022, but I do not see this new text. This is actually very important to have. 

Abstract (and paper): the conclusions that “Overall, this research provides evidence that, in many cases, transportation issues are likely important for local elections.” Can be stronger/more interesting. For example, can you say something about whether constituents care about transportation issues? Is it important to study transportation platforms to understand local election results? Should candidates include transport platforms in their campaign? 

EXAMPLE 2

Thank you for the opportunity to read and reflect on this interesting manuscript. The study engages with innovation district governance (in urban contexts). In general, there is still surprisingly little research on innovation districts and, even less so, on the way this recent iteration of place-based innovation policy is governed. This paper marks a welcome exception. It provides an in-depth analysis of innovation district governance in Melbourne, Australia. Specifically it problematizes a dysfunctional multi-level governance structure informed by an analytical framework that, at its core, mobilizes the notion of innovation jurisdictions. 

All in all, the manuscript presents a well-rounded analysis on a timely but under-researched topic. Its account of governance jurisdictions of innovation districts is applied coherently and convincingly on the Melbourne case study. My main suggestion for improvement relates to strengthening the theoretical purchase of the analysis beyond the Australian context. The distinction between general purpose and task-specific jurisdictions is helpful in identifying dysfunctionalities and coordination challenges in the Australian multi-level governance structure. 

At the same time, these features of the Australian three-tier system are relatively well-known and documented (Phelps et al., 2023). After reading the paper, I am however still left wondering about the wider applicability of the innovation jurisdiction framework for unpacking place-based innovation policy more generally and innovation districts more specifically beyond Australia. As such, the paper would benefit, in my opinion, from a slightly less grounded, more ambitious discussion and conclusion that lifts the gaze beyond Australia’s NEICs. Particularly as the paper sets off by situating the analysis in a discussion on place-based innovation policy. While a brief allusion is made that Australia’s ID policy is heavily inspired by the US, the question remains whether the governance inertia is something that affects ID policies more general or whether this is inherent to the Australian context. Are Barcelona’s 22@ or other totemic innovation districts providing evidence of more conducive innovation jurisdictions in view of more coordinated multi-level governance arrangements? Some commentary on this at the end of the paper would be valued. 

In addition, I have a few more granular comments. 

Page 2, line 26: from which theory/theories does this statement follow? 

Page 3, line 33: the paper has developed a rather marginal link to research on ‘the geography of innovation’. It would be more appropriate to establish a link to the geography of innovation policy. 

Page 4: the theoretical discussion refers both to innovation ecosystems and innovation systems. According to Oh et al. (2016) the former is basically a fad in conceptual/analytical terms. Referring to an eco-system would also evoke implicit implications how such systems are governed. 

Page 5, line 13: what studies are referred to specifically? 

Page 14, lines 41-42: this statement would benefit from some elaboration. Frustration about what, by whom? 

Page 18, lines 29-31: but doesn’t this observation go counter to the earlier (more general) statement that IDs are led by private actors? Also, the analysis remains rather silent on the role and agency of universities in governing IDs. There is a risk that these non-government actors are the elephant in the room and ties to the discussion later on in the discussion / conclusion about embedded autonomy (see Morgan and Marques, 2019). 

References: 

Morgan, K. and Marques, P., 2019. The public animateur: Mission-led innovation and the “smart state” in Europe. Cambridge Journal of Regions, Economy and Society, 12(2), pp.179-193. 

Oh, D.S., Phillips, F., Park, S. and Lee, E., 2016. Innovation ecosystems: A critical examination. Technovation, 54, pp.1-6. 

EXAMPLE 3

Overall, I strongly encourage a revise and resubmit for this paper because I think the data and results are good. You have assembled an interesting and thoroughly analyzed dataset that should be published. However, I do believe that you have a lot of work left to do in turning this manuscript into a publishable paper. Fundamentally, I think you have a hard time telling a cohesive theoretical story with this paper. I believe this problem arises because you have not really put the paper in the broader context of climate change adaptation policy. As a result, the paper reads more as a walk through your survey results. Fundamentally, you need to 1) identify the main theoretical contribution you make to the broader literature on climate change adaptation, 2) reduce the number of hypothesis tests presented in order to focus the paper on the main theoretical contribution you have made, and 3) build out a literature review and discussion that places your main theoretical contribution in dialogue with the existing literature on the subject. 

In my opinion, the main theoretical contributions this paper makes are that you show that willingness to pay for local adaptation climate policies is high, you provide characterization of the amount of people willing to pay by their demographic characteristics and urban/suburban/rural status, and you show that your results are robust to different frames and implementing levels of government. Taken together, the results show that the willingness to pay for climate change adaptation is there whether the implementing government is local or federal and whether or not it is framed as a climate policy. I think exploring the median WTP and percent of people WTP anything is interesting. 

Introduction: 

First, I think it is crucial that you place your paper within the context of climate change adaptation policies. As written, your paper does not seem to make a distinction between adaptation and mitigation with the introduction written to describe climate policies and green policies in general. I would define adaptation policies as those which provide resilience to the negative consequences of climate change and mitigation policies as those which curb emissions. The fifth national climate change assessment discusses this difference. This is a missing reference in your article (USGCRP, 2023). I would firmly put all of the policies you studied in the realm of adaptation. Distinguishing between adaptation and mitigation is important because the way that those policies costs and co-benefits manifest is very different. Mitigation prevents far off future consequences, has cost, and helps solves the underlying problem, whereas adaptation provides current co-benefits to match it’s current costs, but fails to solve the underlying emissions problem. Fundamentally, I’m left wondering, how does your paper add to the existing literature on climate change adaptation. It does, but I don’t know how from reading your paper alone. 

Second, I think you need to describe what the negative consequences of climate change are, especially for cities. While I recognize the need to adapt to climate change, others might not. Characterizing the need for adaptation, and the potential consequences if we fail to adapt, is important context the paper needs to provide. What are the negative consequences the policies you mentioned (energy efficiency, floodwalls, tree plantings, etc.) are trying to prevent? Why are those policies important to pay for? 

Literature Review: 

You are really missing a literature review, and I think that it contributes to the lack of focus in the paper. Your engagement with the prior literature seems limited to some light framing, the political science literature, and other WTP studies, but there is a much broader context here. You characterize your contribution in the general literature on voter preferences, green policy, and climate change generally, but you’re missing the specific dialogues around adaptation. You really need to engage with this literature to show how your paper contributes. Here are some papers I know of on adaptation specifically. You’ll need to do a larger search, but fundamentally I want to know how your study relates to the broader literature on adaptation (beyond willingness to pay) and how willingness to pay studies build on that broader context. Some questions you might answer include, what adaptation policies are local governments deploying, what barriers exist to deploying adaptation policies, and how does your study specifically add to what we know about the popularity of adaptation policy. Here are some papers that I think are good, but you need to do a broader search. Moser and Ekstrom’s barrier framework is very popular. You might start there. 

Moser, Susanne C, and Julia A Ekstrom. 2010. “A Framework to Diagnose Barriers to Climate Change Adaptation.” Proceedings of the National Academy of Sciences 

107 (51): 22026–31. https://doi.org/10.1073/pnas.1007887107. 

Egan, P. J., & Mullin, M. (2017). Climate Change: US Public Opinion. Annual Review of Political Science, 20(1), 209–227. https://doi.org/10.1146/annurev-polisci-051215-02285 

Shi, Linda, Eric Chu, and Jessica Debats. 2015. “Explaining Progress in Climate Adaptation Planning Across 156 U.S. Municipalities.” Journal of the American Planning Association 81 (3): 191–202. https://doi.org/10.1080/01944363.2015.1074526. 

Hamin, E. M., Gurran, N., & Emlinger, A. M. (2014). Barriers to Municipal Climate Adaptation: Examples From Coastal Massachusetts’ Smaller Cities and Towns. Journal of the American Planning Association, 80(2), 110–122. https://doi.org/10.1080/01944363.2014.949590 

Theory: 

The theory section needs some work. First of all, your experimental results are not brought up in the theory section. If you’re going to discuss the level of government and framing effects, you need to lay the foundation at the start (rather than midway through the data section). I know you had a reason to suspect that framing and level of government mattered. How do your null results contradict the prior literature? Why does it matter that a framing or level of government effect doesn’t matter in your experiment? It may have to do with the way that you described the local and direct nature of the benefits. This probably helps us better understand framing and level of government effects. Find a way to let your null results build on and add to prior theory. Second, you need to select a subset of the other hypotheses (probably demographics, partisanship, and community type) and then build out a theory of why these matter that does not just restate the prior literature. In terms of your non-experimental hypotheses, the theory is very briefly described as bullets. If you want to contribute to the literature, you need to provide a bit more evidence that you build on prior work rather than just confirming it. Part of that effort is showing how you build on theory by explaining the theory. I think the median WTP and percent of people WTP anything does build on these prior results. Maybe that could be a way to frame your study.  

Data/Methods: 

I have no issue with surveys deployed on Lucid or Prolific. The data was explained well. It was easy to understand what was included in your dependent and independent variables. You gave sufficient summary statistics to describe the sample. 

Results: 

Overall, you have a ton of different analyses. First, I think you need to refocus the results section on a smaller number of key questions. Second, the results seem a bit inconsistent. Sometimes you bootstrap and sometimes you don’t. Sometimes you give standard errors and confidence intervals and other times you don’t. I think you need to focus on using a consistent set of statistical methods in your results and provide confidence intervals whenever possible. I go through the main analyses below and offer my thoughts on them. 

I think Table 1 would be much better if you presented confidence intervals for the percent of people willing to pay anything, mean WTP, and median WTP. Currently, you only give the standard error for the mean WTP, but you can make confidence intervals for each of these WTP measures. There are many ways to do this for both a proportion and a median. 

I do not think you can extrapolate your results to the US population like you do on page 10. Your sample would have to be perfectly representative and that just cannot be true. Heavily qualify this statement and show the steps in the calculation explicitly. Try to find some way to incorporate an estimate of sampling uncertainty into this estimation (make a confidence interval or estimate a standard error).   

If you want to center the main contribution of your paper as exploring the differences between the proportion of people willing to pay anything, the median WTP, and the average WTP, you could extend your demographic analysis to the proportion of people who are WTP anything and the median WTP. You could use a logistic regression to see what factors predict whether or not someone in your sample was WTP anything and you could figure out what factors predict the conditional median WTP using a quantile regression. If you want to focus your paper on demographic analyses, this could add interest to the paper. 

I am not sure that climate vulnerability or co-partisanship analyses are necessary for this paper. I find them interesting, but they seem underbaked. If you are thinking of cutting some results to focus your paper a bit more on a primary theoretical contribution or set of primary theoretical contributions, I think these could be cut. First, the flood premium analysis is really interesting. I think if you developed it, it could be a stand alone paper. However, you need to figure out what is driving the weird negative correlation between the current/future premiums and the WTP. Is it possible that this relationship is less linear than you’ve estimated? I’d imagine that WTP increases at a decreasing rate with income. Clearly, some people gave very high WTP estimates. Are the outlying WTP estimates driving the negative correlation? Try estimating a log-log relationship (if you don’t want to do a log plus one transformation on the left hand side of the equation you can use a generalized linear model with a log link, like a Poisson regression, see Silva, 2006). A log-log specification could explain the outliers and allow you to estimate a much less linear relationship. Alternatively, it might be reasonable for people who pay more flood insurance to not be willing to pay for flood walls specifically.  It is possible that they may prefer some other strategy. Local governments have a lot of policy options to deal with flooding (see Brody, Bernhardt, Zahran, and Kang, 2009). For instance, a person who lives by a flashy creek may not feel that a flood wall would best protect them. They may prefer some other option. Second, the co-partisanship analysis kind of comes out of nowhere and ends up being null. I am not sure if it’s correct. For one thing, form of government is really central to your question here. Do all of these cities in this analysis have a strong mayor form of government or do they have weak mayors or council-manager forms of government (which often have an elected mayor with limited actual authority)? If the mayors have limited authority, co-partisanship shouldn’t matter. This is a very important control in the context of local politics. I’d imagine there is an interaction effect too. There are a lot of unanswered questions in this analysis, and it doesn't seem central to the paper. In both this and the flood premium analysis, you need more control variables. I don’t think these analyses are ready for prime time and detract from the paper, but your WTP estimates, demographic analyses, and experiments are solid. I think you should build on what’s working in your resubmission.  

I really like the experiment. I think you should make it a more central part of your analysis. You kind of stow it in the end of the results portion, but it estimates a causal effect and had enough observations to be powered. I don’t mind that it has a null result, it is still important. There are a couple of things you should do to incorporate this into your paper. First, I think the hypotheses for the experiment should come earlier. They need to be mentioned in the theory section. Second, I think you can play up and frame these null results in a way that is interesting. It’s common for academics to believe that framing effects matter, but in my opinion they should not. To me, it makes so much sense to me that decision-makers are mostly rational. For instance, most people will understand that a policy that plants trees on their city streets is going to benefit them personally whether the federal government or local government does it and whether it’s framed as a climate change policy or not. I think this is important because it implies that policies that have general benefits to the environment and people’s quality of life, like tree plantings, may find support whether they are framed as a climate policy. Do other studies suggest framing or level of government effects? I think it would be interesting to see if this result differs from other studies. I would build on this experiment. 

Minor Comments for Results: 

Why have you bootstrapped so many of the estimates? Bootstrapping is fine, but there is no reason to doubt the asymptotic standard errors. If you are concerned that your sampling distribution is non-normal, don’t be. You have a large sample, the central limit theorem should kick in. Also, bootstrapping the standard error and then using it to form the confidence interval relies on the assumption of normality as well. So, it doesn’t fix the non-normality problem if that was your concern. If you are going to bootstrap, mention 1) how you resampled the data and 2) how you formed the bootstrap confidence intervals from the resamples. It’s not clear how you’re forming the bootstrapped confidence intervals. You can’t just say you bootstrapped. There are many choices, and they all come with tradeoffs. Bootstrapping opens an unnecessary can of worms, and it makes your results kind of inconsistent (see Hesterberg for what a big can of worms bootstrapping really is). I think it’s better to just use some type of robust standard errors for your regressions. They are valid and easy for all of your readers to understand. 

When resubmitting the manuscript, please make sure all the tables and figures are cleanly formatted. There are tables and figures which are not ready for publication. For instance, in Figure 3, I can still see the underscores used in the variable names. Your correlation charts in the appendix are raw output from a statistical program. It is important that all the tables and figures are attractive, not just the main ones. Please go through and make sure the labels are consistent and attractive, the numbers are easy to read, and so on. Also, please report the joint significance test, R-squared values for your regressions, and the number of observations that appeared in each regression. 

Discussion: 

Once you figure out how your paper builds on the broader adaptation literature, you need to discuss it here. To fix this section, you need to fix the literature review and theory. 

It makes sense in your discussion that voters are more WTP for your adaptation policies with current co-benefits than mitigation. This is one of the important distinctions between adaptation and mitigation policy. 

References Mentioned: 

USGCRP, 2023: Fifth National Climate Assessment. Crimmins, A.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, B.C. Stewart, and T.K. Maycock,Eds. U.S. Global Change Research Program, Washington, DC, USA. https://doi.org/10.7930/NCA5.2023 

BRODY, SAMUEL D., et al. “Evaluating Local Flood Mitigation Strategies in Texas and Florida.” Built Environment (1978-), vol. 35, no. 4, 2009, pp. 492–515. JSTOR, http://www.jstor.org/stable/23290000. Accessed 29 Sept. 2025. 

Hesterberg TC. What Teachers Should Know About the Bootstrap: Resampling in the Undergraduate Statistics Curriculum. Am Stat. 2015 Oct 2;69(4):371-386. doi: 10.1080/00031305.2015.1089789. Epub 2015 Dec 29. PMID: 27019512; PMCID: PMC4784504. 

J. M. C. Santos Silva, Silvana Tenreyro; The Log of Gravity. The Review of Economics and Statistics 2006; 88 (4): 641–658. doi: https://doi.org/10.1162/rest.88.4.641 

EXAMPLE 4

This paper quantitatively and qualitatively examines urban fiscal crisis in three U.S. cities. The author(s) ask: 
1. How GFC and COVID-19 impacted how they understood their situation 
2. How the crises revealed fiscal concerns 
3. How external global crises shaped preexisting “internal” fiscal challenges 
 
They argue that a processual and relational framing is needed to understand urban crises. 
 
Although the paper clearly draws from significant research, it does not fully answer the questions it poses or the claims it makes. To start, the paper doesn’t answer “so what?” Why should readers care about these cities or this topic? What is the bigger picture here? What does answering any of these research questions actually tell us? And who is the “us?” 
 
Despite the presence of quantitative and qualitative evidence, the case studies are overly generic and do not offer new perspectives on the urban political economy/governance. There doesn’t seem to be a thread that unites the cities. The timelines don’t precisely line up. San Jose, for example, goes back further. Nashville deviates into other crises. Buffalo’s novelty falls flat. Moreover, the paper draws on 44 interviews but relies heavily on newspaper articles rather than direct quotes. Additionally, the tables and charts are not well visualized and weaken, rather than strengthen, the paper. 
 
Specific suggestions for a revised manuscript are as follows. 
 
Literature review and theoretical contribution. 
The paper argues it is necessary to have a “processual and relational framing of urban crises.” However, the literature review does not establish this, nor is the methodology for processual and relational analysis defined, and it is not revisited in the conclusion. It is unclear what this phrase even means. 
 
A greater connection needs to be made between crises and the “fiscal.” The author(s) overtheorize crises to the detriment of making clear what, why, and how urban crises are fiscal crises. Newer, more recent literature, such as “fiscal geographies” and related fields, bridges these connections. Although the author(s) mention the debates in austerity urbanism and pragmatic municipalism, these are just two narrow slices of a bigger conversation, including recent literature around COVID-19 and municipal budgets. Without a well-defined body of literature, it’s unclear who the audience for this paper is and what theoretical gaps and contributions the paper fills/makes. 
 
Methods 
What is a third sector informant? Page. 13 line 31. 
Given the 4-part typology of cities they use, why do the author(s) include a 4th city in their analysis? 
 
Feedback on individual case studies: 
Buffalo 
In many ways, the author(s) have buried the lede in this case study. For starters, more recent background is needed before throwing the reader into the fiscal weeds. The narration of “crises” comes in later, and more specifically, the general story of Buffalo comes in the last sentence of the section (p.20, lines 28-29). This line isn’t novel, which makes the case justification about Buffalo seem less important than the author(s) claim. 
 
The real story seems to be around intergovernmental transfers from the state to the city. As it reads, this story is not clearly spelled out. 
 
Nashville 
Why are there footnotes to articles that should be in the reference list? 
If the city is growing, how does it have a budget shortfall? If housing is unaffordable, I’m assuming property values have increased. Therefore, shouldn’t property tax revenue also increase? If not, why? 
 
What are these so-called “demands for expenditures…frequently associated with U.S. Northern cities?” And would Buffalo be one? 
 
Line 31-21 on p.23 is a sweeping generalization that is not supported elsewhere (i.e., literature review) in the paper. Moreover, how are these “crises” uniquely urban? 
 
San Jose 
How much does it cost to jail a homeless person? 
How do commercial property taxes differ from residential property taxes? 
The San Jose example returns the reader to a scalar question about the role of the subnational state and the municipality (i.e., Prop 13). It could connect back to Buffalo, but more details would need to be given. 
 
Figures, charts, and tables 
Double-check the tidiness of your charts and graphs. There are errant capitalization, spacing, and DPI problems. 
 
Figure 2 is a confusing mashup of two charts that would be better represented by separating them. State aid as % of revenues is confusingly transplanted on top of the chart. I would recommend keeping state aid and general revenues and then narrating (in text) how state aid went from ~40% to ~22%. 
What’s going on with Figure 6? And Figure 8? Make sure all of the graphs are using the same font, organization, etc. Figure 6 shouldn’t include 2D shading. Figure 8 is chaotic and should be two charts. 
 
Why does Nashville get a timeline, but no one else does? Better organization and visual representation across the figures would lend credence to justifying the case study selection. 
 
Charts 3, 5, 7—unless you put these together, it’s hard for readers to draw comparisons between them. As they stand, there isn’t anything surprising or novel about these terms. They just seem like political rhetoric around spending. Does what you’re showing here best support the nuance you’re trying to show? 

EXAMPLE 5

This paper looks at faith-based efforts to fund, design, and build affordable housing units using religious lands or spaces once occupied by churches/congregations. Affordable housing issues are numerous, so I applaud the authors in targeting a space in this area that is not as much researched (as evidenced in the literature section). The article has both survey and interview data, which is helpful in research that covers newer spaces (or at least not as frequently studied). There are some parts that could use some work to improve the paper for publication. These include, framing the research, using the proposed theoretical framework to construct the findings, and some editing/graphics to clarify the specific vocabulary used in the paper. 
 
1) Title- I would rethink this, it undersells what you are doing in the paper- focus more on the convening role of faith-based housing groups/churches providing affordable housing. Think of it this way, do faith-based affordable housing endeavors provide something new and or different to increase the number of affordable housing units? (or even the likelihood of getting such projects approved and built). 
2) Intro- would benefit from better framing to orient the reader before getting into the specifics of this research. I would suggest some overview of affordable housing, potential solutions that have been tried, how the space has mostly been private companies and or government and where faith-based groups may have a unique space/edge to fill. Then go into this area of housing and what we can learn from their successes- or something like this. 
3) Overall- this paper needs a tighter framing and more connection to the theories the authors are drawing on- these must be better incorporated in a theoretical section and then with how the findings are constructed. Right now, the literature section is more context than literature- so maybe make it “study context/background” and then have theoretical background that is closely tied to the findings. 
4) Do urban based standards for planning contribute to success of projects? Or are they just a basis for comparing projects so that those driven by faith-based groups and those that are not can be seen as equally designed? Is this section necessary or just so you can acknowledge that the projects are of equal quality and design as those not produced by faith-based organizations? 
5) The following comment on page 10 “We will use community organization social capital constructs by Fernandez & Alexander (2017) to measure how congregations mediated social capital in the development planning process and determine whether it was associated with successful achievement of urban planning standards?” Do you also mean successful affordable housing developments that are also aligned to standards? This seems to be the papers contribution- using this framework to see how faith-based organizations have used/draw on and asserted their social capital in different ways. 
6) The interview and survey combination is a great way to get triangulate the data. The thing is, the story gets lost in all the sections rather than relying on the framing of community engagement through mediating and generating. It seems like the data is there to really tease out the theories and the parts of the theory. Right now, it references the theories without as much bringing them out in the data. 
7) Is there a way to communicate some of the findings in a table format? 
8) With the property types- are their differences in social capital used depending on the property types referenced on p. 18 -19 of the draft copy? 
9) Is there a connection between the social capital use/efforts reported and the barriers referenced- in other words, did those interviewees who referenced barriers also then report different types of social capital use, or applying the framework, use mediating and generating roles to overcome them? This seems to be answered somewhat in the “successful strategies” section, but again, the findings need some reworking to shape the paper more towards the contribution it is making to theory. The following sentence on p. 32 really captures the contribution: “Forms of social capital used by religious organizations to gain community and political support for affordable housing deepen our understanding of the important contribution religious organizations make in representing neighbors needs in the policy area and fostering civic participation.” 
10) This paper is overall an interesting topic and one that should be explored more. I would encourage the authors to rework the framing and resubmit. 

Reject

EXAMPLE 6

I recommend that this article should not be published. Its framing betrays a surprising ignorance of basic research that has been conducted on Chinatowns, (especially Manhattan Chinatown) over decades as well as issues facing Chinatowns for more than a century. The interface of residents and tourism, for example, faced Chinese Americans as early as the late 19th century on the West Coast and in a similar time. frame across the Americas; look at Ivan Light’s classic (1976) work decades ago. There have been hundreds of studies on Chinatowns worldwide by geographers, anthropologists, architects, planners, public health advocates, historians and many others, many based in Chinese community action. Treating the intersection of community and tourism as a novelty and proclaiming the article as one of the first to look at placemaking is self- aggrandizing and off-putting for scholars in the field. To then add “This study addresses this imbalance by amplifying the often-overlooked perspectives of Chinatown residents” also overlooks not only decades and scores of inclusive academic studies but also reports from Chinatown activists from newspapers to the AALDEF. Given these basic lacunae, the article seems to be the work of junior scholars (students?) relying on analytics of global tourism while failing to engage basic research on Manhattan Chinatown (Peter Kwong). It ignores the scholarly dialogues on which we all build. Hence I have tried to write to guide the young authors looking past specific errors and omissions which are numerous and problematic. 
 
Let us consider the abstract alone which refers to the Manhattan Chinatown after more than a century of development as an area “undergoing urbanization and multicultural commodification.” Neither term has a clear meaning but “undergoing urbanization” seems completely wrong for an area enmeshed for centuries in a city that has been active since the Dutch settlement and has hosted Chinese for 150 years. Did the authors simply mean urban change? Is this unique to Chinatown?  

Then, the authors classify what those whom they later identify as participants in a broader survey as “marginalized residents.” Does this homogenization follow from residence or race? What about Chinese American elites/power brokers, landlords, store owners and professionals?  Who are stakeholders in the community?  

Finally, a phrase like “urban policies that prioritize multicultural branding over equitable development” leaves vague the question of agency –implying an omnipotent outside city planner in decisions that also involve Chinese owners and leaders. It is also unclear how multicultural branding (signs in English and Chinese?) does not include serving Chinatown’s often bilingual and culturally flexible residents as well as both as customers and laborers.  

Moreover, who imposes equitable planning in any divided community? Again, is this a unique solution for Chinatowns or part of a wider urban theoretical position? An axiom or an argument? The narrow disciplinary definition of place ignores the political inputs from many of fields and scholars (David Harvey, Neil Smith, Lefebvre) beyond recent tourist studies, making it seem as if there are few studies. Yet, even a simple Google search of Chinatown + placemaking reveals myriad active debates, webinars, design collectives and legacies of earlier work. 
 
Unpolished conceptualizations resound throughout the piece and undercut it. The problematic assumptions that authentic Chinatown stakeholders are marginalized or poor or, indeed, homogeneous, seems to lead to the idea that what seems an unstructured sampling is the best tool to gather voices (as if Kwong had not spent decades explaining issues of class and power in Manhattan’s Chinatown). For such extensive data gathering, the lack of social grounding in the presentation, for example, allows the author(s) to overlook histories of intra-ethnic exploitation based on multicultural ties in realms such as restaurants or sweatshops not only in Manhattan but also in other NYC Chinatowns like Sunset Park or tensions between older Cantonese stakeholders and newer Fujienese.  

One might still hope that the data would be of value given the time and manpower put into the project in 21 interviews in 2022 and 476 surveys collected in 2023 plus observations in businesses. This looks like a massive study, but the communication of results does not convey any such authority. While the author(s) note the initial problems of contacts and trust for surveys they give us no information on how interviewees were recruited, much less the script of such extensive conversations or even the language(s) in which they were conducted. Recruitment for surveys through gatekeepers introduces other issues but given this, what was the goal of the survey pool: vague breadth rather than structuring a complex community with multiple roles and agencies?  

One third of those interviewed seem to powerful stakeholders outside Chinatown: How were varied roles weighed in structuring interpretation? In fact, we are given few unsystematic examples (from which source?), quotations with erratic partial identifiers which refer to generation, leadership role but do not even consistently not gender, language or education, etc. Nor do we glimpse questions beside “How would you describe Manhattan Chinatown to others?” where “others” might include Chinese in the U.S and China as well as many different kinds of people. Even this question demands clarification of whether the author(s) talking about experience or perceptions among residents (was this asked in Mandarin, Cantonese, Fujienese or English). Similarly, we are provided with quotations in which “first-generation” Chinese immigrants talk about language without even knowing their point of orientation, as links to presumably English-language tourist comments on “friendliness” and expectations of communication. One hopes there are more nuanced data in such an extensive project, especially dealing with issues like multiple languages and Chinese cultures in Chinatown over generations, that are simply omitted here. In other words, as a portrait of Chinatown attitudes and experiences, this feels sadly simplistic. 
 
The balancing data are even more problematic. Despite one reference to the value of TripAdvisor as a source in tourism studies and its impact on tourism, do web postings without context provide adequate data by their sheer quantity? Would a systematic review of guidebooks, for example, not have provided equal and more nuanced views? (Which could be located in American sources as well as European and Chinese perspectives from outside). Or social media, which offer conversations among various participants on Chinatown issues? I assume investigators chose systematic questions and topics for surveys and interviews. In counterpoint, what are the presumed prompts, though, for TripAdvisor other than a limit of 20,000 characters? Do these sets of data actually intersect? Since many TripAdvisor posters are regulars, are there patterns of celebration, complaint or on particular issues that characterize individuals or groups? It is especially striking that while Chinatown residents talk about food and visitors value it, the researchers did not look more deeply into TripAdvisor’s food reviews, a primary function of the site as a tourist destination. Even banal statements might actually be ambiguous: Canal Street, for example, has become a market for imitation designer goods sold by Chinese and South Asian store owners and African street vendors whose very cachet is their illicit cheapness.  

In the end, data from mostly offhand remarks on TripAdvisor should not be understood without nuanced contextualization or data from other sources that contribute to the discourses of Chinatown. Finally, the author(s) seem to make a primary claim of importance around the comparative framework of tourists on TripAdvisor. Many Chinese have knowledge of other Chinatowns from news media, television, friends and travel as well as their own lives and movements. Were the interviewees and surveyed respondents actually asked how Manhattan Chinatown compared with Flushing, Sunset Park or Bensonhurst? Philadelphia, DC or Chicago, much less London, Bangkok or Kuala Lumpur? 
 
The data sets thus seem neither connected nor complementary, hardly representative of concrete populations and in the end, results prove rather banal. Nor do the data as presented speak to any deeper understandings of community and context. One can easily find New Yorkers in any neighborhood who complain about trash, security and other stereotypical urban ills, in solid middle class neighborhoods and those which are diverse in race and ethnicities, while homogenous in terms of class. As while cheap food may be important for the Chinese (and others), did no one provide answers we know are important to residents from every monograph on New York Chinatowns –sociability, language flexibility, institutions, ownership, memory, et cetera? The absence of compelling and clearly presented data and a lack of engagement with rich traditions of scholarship on Chinatowns, especially Manhattan, would be problematic even in an undergraduate paper. While the author(s) seem committed to the project given the scale of their data collection, they need thought and guidance in moving ahead to engage exciting issues in contemporary urban studies already being posed by Chinatown scholars and residents alike. 

EXAMPLE 7

Thank you for the opportunity to review this article. The authors’ research question is intriguing, and the topic certainly timely. However, I am not entirely convinced that, under the current framing, it fits the scope of the journal, given the lack of focus on urban issues or a clear urban sample. Even assuming the article clears this hurdle, perhaps with different framing, there are fundamental issues with the data and methodology that undermine the authors’ argument. 

First, the descriptive characteristics of the actual study sample are unclear. The authors describe the distribution of the control variables in the full survey sample, but not in the much smaller samples used for the actual models. It is also not clear why different models in the same tables have slightly different samples (I am assuming it is due to missing values in the covariates). 

On the topic of covariates, they are all measured at the time of the survey, not at the time of the contact with the criminal justice system, which for the majority of the sample was more than 4 years prior. This is a very serious issue for all but the sex variable. Age may be the most obvious, but education and household income can also change significantly over time and could be influenced by the very outcomes being measured. Additionally, residential location is not fixed in time either and respondents that moved after the criminal justice contact being reported will have their cases misclassified. 

In terms of outcomes, what is being captured by the survey questions is not quite what the authors present. The question about prison/jail time simply asks whether the respondent spent time in prison/jail, including as a juvenile, without more information in terms of duration or whether such incarceration happened after trial. It is quite possible that many in this category had brief detention periods while awaiting arraignment that should not be directly attributed to prosecutorial action. For the probation outcome, when prosecutors don’t “win” probation for the defendants, it is not immediately obvious what the alternative is. The interpretation of whether a “win” is good for the defendant is quite dependent on whether not-probation means incarceration or no supervision at all. 

In terms of the presentation of the results, the interpretation of the interaction terms in a logistic regression is not straightforward, and calculated probabilities depend on the other covariates, given the nonlinearity of the model. This nuance is absent from the text. Relatedly, Figures 1 and 2 would benefit from captions/notes to aid interpretation. 

Finally, there are some key pieces of information that are absent from the data and greatly limit the results. First, we have no information about the prosecutors (or judges) beyond their perceived race. Without knowing their age, years of experience, whether they were part of a specialized unit, and similar considerations, we cannot confidently state these outcomes have anything to do with their race. Additionally, we have no information about the actual criminal charges in each of these cases. There is no way of knowing if these groups are comparable when we don’t know if the offenses at hand were violent, property, sexual, misdemeanors, or felonies. 

In fact, these missing pieces in term of case characteristics also preclude testing of the key assumption the authors make when discussing their theory: that minority prosecutors charge fewer marginal cases. That idea is an intriguing one, but there is not enough information in these data to directly address it. The article’s conclusion does acknowledge some of this, but that brief discussion is not enough. As an alternative framing, the authors might consider engaging further with Gunderson (2022), which they do cite in the introduction but do not revisit, since that paper found opposite results. 

EXAMPLE 8

This manuscript uses two large-scale national surveys that capture individual-level willingness to pay (WTP) and public opinion toward local climate policies in the United States. Its primary contribution lies in shifting the focus of climate policy study from policymakers and institutional actors to the public’s opinion. Much of the existing literature on climate governance emphasizes decision-makers’ preferences, institutional capacity, and formal policy design, whereas this study redirects attention toward how citizens perceive and value local climate action. This perspective is valuable because it highlights the importance of bottom-up dynamics in shaping climate governance and points to the potential for local public opinion to drive policy change. Another strength is the survey design’s explicit separation of policy costs and benefits, which helps reduce the bias inherent in public opinion studies that measure only attitudes toward policy benefits. By capturing WTP for specific local climate policies and disaggregating policy dimensions, the paper provides a useful descriptive account of how citizens evaluate the trade-offs involved in climate governance. 

Despite these strengths, the manuscript has some theoretical and conceptual weaknesses. The research appears to pursue three main questions: (1) how WTP varies across policy types, including expansions of existing policies versus new initiatives; (2) what demographic, political, and contextual factors shape WTP and policy prioritization; and (3) whether framing policies as “climate policies” or assigning responsibility to local versus federal governments affects WTP. However, the literature review and theoretical framework provide only minimal support for these questions. The discussion of existing scholarship is largely enumerative rather than synthetic and does not build toward clear hypotheses or a conceptual model. For instance, the analysis of WTP for existing versus new policies lacks theoretical justification beyond the intuitive expectation that voters will prefer familiar policies. Without a stronger theoretical grounding, the finding that voters are more willing to pay for expansions of existing policies adds little to our understanding of climate policy support. Similarly, the set of predictors included in the regression model, such as age, income, partisanship, community type, and climate vulnerability, is drawn directly from existing studies but is not integrated into a new explanatory framework. As a result, the study offers a limited theoretical contribution beyond replicating known relationships in a new context. Finally, the third research question, which is potentially the most innovative, is also the least well developed. The idea that framing and government level could influence WTP is compelling, but the manuscript does not theorize why such differences might arise or how they might interact with trust, partisanship, or perceived policy scale. Without such theoretical development, the null findings from the framing experiment remain difficult to interpret and add little explanatory value. 

Concerns also arise in the empirical strategy used to address the research questions. The analysis of WTP determinants relies on individual-level regression models, which is appropriate but remains descriptive rather than explanatory. Beyond this, however, most of the empirical evidence presented for RQ1 and RQ3 is based on simple descriptive statistics, such as comparisons of means and medians, or mean difference tests accompanied by confidence intervals. While such analyses can be informative, they do not provide strong evidence for the claims made. In particular, the absence of statistically significant differences in the framing and level-of-government experiment could stem from insufficient statistical power, weak treatments, or uncontrolled confounding factors, none of which are addressed in the manuscript. Moreover, the reliance on unadjusted mean comparisons limits the ability to assess whether the observed differences hold once demographic, political, or contextual factors are controlled for. Without more rigorous modeling or robustness checks, the empirical results remain suggestive rather than conclusive. 

In conclusion, the manuscript’s effort to capture individual-level attitudes toward local climate policy through large-scale surveys is commendable, and its emphasis on public opinion rather than policymaker preferences is a welcome shift in the literature. However, the paper falls short of making a significant scholarly contribution due to its weak theoretical framing, underdeveloped research questions, and reliance on largely descriptive empirical analyses. The most promising element, the exploration of framing and government-level effects, remains under-theorized and methodologically thin. To strengthen this manuscript, the authors would need to develop a clearer conceptual model linking public opinion to specific mechanisms, formulate explicit hypotheses grounded in the literature, and employ more robust empirical strategies to test them. As it stands, the manuscript offers a useful descriptive snapshot of public attitudes but lacks the theoretical and analytical depth necessary for publication in this journal.