-->PONE-D-25-67060-->-->Measurement of Public Space Justice in Traditional Villages with Coexistence of Old and New Based on Villagers’ Perceptions-->-->PLOS One

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Reviewers' comments:

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1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #1: Partly

Reviewer #2: Partly

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-->2. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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-->5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #1: The manuscript is partly technically sound. It presents a clearly described two-site field survey (314 valid responses collected through face-to-face interviews in Zhushan in October 2024 and Dabitou in April 2025) and reports a standard set of measurement checks, including reliability and validity indicators (e.g., Cronbach’s alpha, KMO/Bartlett, composite reliability/AVE, and factor loadings), alongside structural path estimation using bootstrapping in SmartPLS (1,000 subsamples). Nevertheless, several internal inconsistencies and gaps in evidence weaken confidence that the conclusions are fully supported by the reported analyses. In particular, the manuscript mixes and conflates reporting conventions from PLS-SEM and CB-SEM, contains a mismatch between abstracted and tabulated coefficients, and advances comparative claims (e.g., “outperforming” one-dimensional models and “spatial differences” between villages) without clearly presenting the required baseline models, statistical comparisons, or formal tests.

First, the statistical methodology is not reported consistently. While the manuscript describes the use of SmartPLS and the PLS algorithm with bootstrapping, it simultaneously reports CB-SEM-style global fit indices such as χ²/df, CFI, TLI, and RMSEA. This blending of paradigms is confusing and makes it difficult to assess technical adequacy. The authors should explicitly state whether the primary analytical framework is PLS-SEM or CB-SEM and report diagnostics appropriate to that choice. If both approaches were genuinely used (e.g., AMOS alongside PLS, as suggested in the acknowledgments), the manuscript must clearly justify the dual approach, specify which software was used at each stage (measurement versus structural model estimation), and present results in a coherent, methodologically aligned manner.

Second, there is a key inconsistency between the abstract and the results section. The abstract reports the effect of distributive justice as β = 0.58, whereas the structural model table reports β = 0.45 for Distribution Justice predicting overall justice perception. This discrepancy should be corrected throughout the manuscript so that all reported coefficients match the final model output.

Third, the claim that the proposed framework “outperforms traditional one-dimensional models” is not currently demonstrated. Although the model is reported to explain 63% of the variance (R² = 0.63), the manuscript does not provide the results of any one-dimensional baseline models (e.g., Recognition-only, Distribution-only, Participation-only), nor does it report an explicit model comparison using a consistent criterion (e.g., ΔR², predictive performance, or other appropriate SEM comparison metrics). Without such baseline estimation and comparison, the conclusion of “outperformance” is not supported by the evidence presented.

Fourth, the manuscript’s claims of “important spatial differences” between villages are not adequately substantiated with explicit quantitative testing. The abstract advances mechanism-level explanations (e.g., capital-driven monopolies suppress participation in Dabitou, while governance structures strengthen recognition in Zhushan), and the Results/Discussion provides narrative “case evidence,” yet it remains unclear what statistical tests support between-village differences. If the authors intend this as a quantitative comparison, they should report per-village sample sizes and conduct appropriate statistical analyses (e.g., mean comparisons on constructs, multi-group analysis in SEM, and—crucially—measurement invariance testing where relevant). If the inference is primarily qualitative, then the paper should describe the qualitative design, sampling, and analytic procedures more rigorously and temper causal language accordingly.

Fifth, measurement development is insufficiently transparent and contains contradictions. The manuscript states that 25 items were reduced by removing 9 low-loading items, leaving 16 items; however, it later refers to “removing two items” while still retaining “the remaining 16 items,” which is mathematically inconsistent unless intermediate versions existed. In addition, several retained indicators have notably low factor loadings (e.g., P3 = 0.53 and distribution indicators as low as ~0.61), despite the earlier claim that low-loading items had already been eliminated. The authors should provide a clear item-retention flow (initial pool → pretest modifications → final instrument), explicitly list removed items at each step, justify the retention of lower-loading indicators (or revise/remove them), and demonstrate whether conclusions are robust to alternative measurement specifications.

Sixth, the proposed Spatial Justice Index (SJI) weighting scheme appears potentially circular and requires stronger justification. The index is presented as SJI = 0.45×Distributive + 0.32×Recognition + 0.23×Participation, apparently derived from standardized model effects. This risks overfitting because the weights are extracted from the same sample/model used to validate the index, yet the index is framed as an operational tool. The authors should strengthen the rationale for the weights (normative and/or empirical) and include sensitivity analyses (e.g., equal weights, alternative weighting schemes, or cross-validation). If model-derived weights are retained, the index should be presented as context- and sample-specific rather than generalized.

Finally, several additional points should be addressed to strengthen rigor and presentation. The manuscript reports bootstrapping with 1,000 subsamples; this is often considered minimal in SEM practice, so increasing the number of resamples and reporting confidence intervals for path coefficients would improve stability and interpretability. Moreover, some proposed policy thresholds (e.g., “30% attendance” or “50% agenda items co-proposed”) read as normative and are not clearly derived from the presented data, so these should be justified empirically or softened in tone. The limitations (e.g., underrepresentation of youth and reliance on perceptual survey data) are appropriately acknowledged, but the abstract and discussion should reflect these limitations more consistently by avoiding overly strong causal language and by framing findings as associative rather than deterministic where warranted.

Reviewer #2: 1. Spatial Justice Index (SJI) derivation is statistically invalid – Path coefficients cannot be directly used as policy weights. Remove the SJI formula or clearly state it is illustrative only, with proper justification.

2. Severe age bias undermines generalizability – Only 9.6% of respondents are under 25. Temper claims about global scalability and frame findings as specific to aging, low-education rural populations.

3. Village comparison lacks statistical support – Pooled SEM cannot support claims of differences between Zhushan and Dabitou. Either conduct multi-group analysis or reframe as qualitative observations.

4. Low factor loading for item P3 (0.53) – This is below the conventional threshold of 0.60. Report model fit without P3 or justify its retention.

5. Insufficient theoretical justification for rural-urban adaptation— Explain why rural justice dynamics differ from urban (depopulation, tourism, aging) with references to rural geography literature.

6. Missing chi-square p-value – Report the p-value for the chi-square test (not just χ²/df = 2.31) and discuss implications for model fit.

7. Oral consent details insufficient – Specify whether consent scripts were IRB-approved, how comprehension was verified, and how capacity was assessed for elderly participants.

8. Data availability statement ambiguous – Clarify whether raw survey data (314×16) will be published as supporting information or provide access conditions.

9. Social desirability bias not addressed – Face-to-face interviews by researchers may bias responses about governance. Add a limitation paragraph and describe mitigation strategies.

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Reviewer #1: Yes: MOHD NORBAYUSRI BAHARUDIN

Reviewer #2: No

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Measurement of Public Space Justice in Traditional Villages with Coexistence of Old and New Based on Villagers' Perceptions

PONE-D-25-67060R1

Dear Dr. Deng,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Jamil Afzal, Ph.D, Post Doc

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.-->

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

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-->2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #2: Yes

Reviewer #3: Yes

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-->3. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #2: Yes

Reviewer #3: Yes

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-->4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #2: Yes

Reviewer #3: Yes

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-->5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.-->

Reviewer #2: Yes

Reviewer #3: Yes

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-->6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)-->

Reviewer #2: (No Response)

Reviewer #3: Comment:

The authors have submitted a thoroughly revised manuscript that convincingly addresses the substantive methodological and theoretical concerns raised during the initial review. The revisions demonstrate a serious engagement with the feedback, significantly strengthening the paper's rigor, clarity, and scholarly contribution.

The key improvements that warrant acceptance are:

1. Methodological Rigor and Transparency: The authors have decisively clarified the analytical framework, explicitly stating the sole use of PLS-SEM and removing all inappropriate CB-SEM fit indices. The addition of a dedicated "Analytical Approach" subsection, the correction of terminology, and the inclusion of PLS-specific metrics (e.g., Q²) bring the methodology reporting to a high standard. The transparent presentation of the item-screening process (new Table 2) and the justification for retaining lower-loading indicators (e.g., P3) based on sensitivity analysis and theoretical grounds are commendable.

2. Accurate and Consistent Reporting: The critical inconsistency in the beta coefficient for distributive justice (Abstract vs. Results) has been corrected throughout the manuscript (β=0.45), ensuring internal consistency. All claims have been carefully tempered to align with the evidence.

3. Appropriate Framing of Findings: The authors have correctly reframed claims about "outperforming" one-dimensional models to more accurately highlight the value of their multidimensional approach in capturing interconnected perceptions. Crucially, they have reframed inter-village comparisons (Zhushan vs. Dabitou) as qualitative observations based on case evidence, adding a clear methodological statement that formal multi-group analysis was not conducted due to sample size. This is a responsible and appropriate interpretation of the data.

4. Theoretical Strengthening: The new paragraph in the Introduction, "Why Rural Spatial Justice Requires Distinct Theoretical Treatment," provides a much-needed and robust justification for adapting urban-centered justice theory to rural contexts, effectively addressing a core theoretical gap.

5. Acknowledgment of Limitations and Refinement of Claims: The authors have significantly expanded the Limitations section, thoughtfully addressing critical issues such as sample age bias, social desirability bias, and the illustrative (non-generalizable) nature of the proposed Spatial Justice Index (SJI). The language throughout the manuscript has been tempered, replacing overly causal claims with more measured interpretations.

6. Ethical and Data Transparency: The ethics statement has been expanded with sufficient detail on the oral consent procedure, and a clear Data Availability Statement has been added, meeting journal standards.

In summary, the revised manuscript is now methodologically sound, theoretically grounded, and clearly presented. The authors have successfully transformed a manuscript with potential into a robust and publishable research article that makes a valuable contribution to the fields of rural geography, spatial justice, and traditional village studies. The study's proposed three-dimensional model offers a practical, empirically validated tool for assessing justice perceptions in transitioning rural landscapes.

Therefore, I recommend acceptance of the manuscript in its current form.

Decision: Accept

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Reviewer #2: Yes: Jalil Ahmad

Reviewer #3: Yes: Dr. Maria Qayyum

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