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This review is the result of a virtual, collaborative live review discussion organized and hosted by Alan Colin-Arce and Monique Grenier on March 16, 2026, as part of the PREreview Champions Program 2026 and the Open Science Community of Victoria. The discussion was joined by 16 people. The authors of this review have dedicated additional asynchronous time over the course of two weeks to help compose this final report using the notes from the Live Review. We thank all participants who contributed to the discussion and made it possible for us to provide feedback on this preprint.

Summary:

The paper seeks to operationalize Pierre Bourdieu’s concept of symbolic capital using bibliometric and network analysis methods. The study examines how symbolic capital is distributed among members of journal editorial boards in the field of sustainability science and what structural inequalities emerge within these editorial networks.

To address these questions, the paper applies network analysis to examine hierarchies of symbolic capitalism capital in the field of sustainability science. To measure the distribution of symbolic capital, the author combines eigenvector centrality and Gini coefficients to assess inequality within the field, particularly focusing on editorial board interlocks among 30 journals. The study also provides access to code and a sample dataset via GitHub repository, supporting transparency while addressing ethical constraints related to sensitive data. This approach assumes that researchers holding multiple editorial positions—especially alongside other central actors—accumulate higher symbolic capital due to recognition within the field.

The findings show a strong geographic concentration of symbolic capital rather than a globally distributed structure, with institutional concentration among elite universities in the Global North. Women were also underrepresented among the interlocking editors. This concentration suggests limitations in the diversity of perspectives represented in sustainability journals. However, these findings should be interpreted in light of the journal selection criteria and the focus on a single disciplinary field. The paper also provides a typology for classifying journals based on the distribution of symbolic capital and levels of inequality.

Overall, this operationalization of Bourdieu’s concept of symbolic capital offers a valuable quantitative approach to understanding inequalities in academic publishing and could be extended to other disciplines. Beyond its appeal for researchers in information science and bibliometrics, this study may be particularly relevant for journal editors and stakeholders seeking to improve diversity and inclusivity in editorial governance.

List of major concerns and feedback:

Overall, the paper is well-organized and comprehensible. The contributions are clearly stated, the methodology is detailed, and the data supports the interpretation of the results. However, there are a few suggestions that could strengthen the paper:

1. We recommend incorporating a more critical reflection on the criteria used to select the journals included in the study. While most of the sources were selected from a previous study, the manuscript would benefit from a clearer justification of what qualifies these journals as “leading” or “historically significant”. Furthermore, it seems that most of these journals are Anglophone and published in Europe or North America. This selection may introduce a structural bias that partially explains the observed geographical concentration of editorial power. Explicitly acknowledging this potential bias would strengthen the interpretation of the findings.

While the limitations section acknowledges that regional journals were excluded from the analysis and that they may exhibit different editorial dynamics, the rationale for their exclusion should be more explicitly discussed, including its implications for the generalizability of the results.

1. The network analysis approach seems appropriate for studying how symbolic capital is distributed in editorial boards. However, the study treats all editorial board positions as equivalent, even though roles such as editor-in-chief, associate editor, or managing editor may have different levels of influence. These assumptions should be made explicit and critically discussed, as it may affect the interpretation of centrality measures and the distribution of symbolic capital. Alternatively, the author could consider differentiating editorial roles or outlining this as a key avenue for future research.

2. The results section provides extensive evidence for geographic and gender biases in editorial board compositions. However, the analysis of institutional concentration remains comparatively underdeveloped. The only results presented on institutional concentration are found in one paragraph at the end of section 3.1. Providing a more systematic analysis—such as a table listing the most represented institutions—would allow for stronger and more transparent conclusions regarding institutional inequalities. This could be included in an appendix or on the GitHub repository.

List of minor concerns and feedback

• Some tables and figures could be further refined to improve clarity and accessibility. We suggest expanding Table 1 to include additional contextual information, such as the number of editors, publisher name, and the country of each journal, which would facilitate a more comprehensive understanding of the dataset. In Figures 1-3, the degrees/number of editors (the size of the circles) are difficult to differentiate. We suggest making the differences in size more noticeable to aid in the interpretation of the figures. Figure 3 could also be improved with clearer labeling or slightly more explanatory captions to help readers unfamiliar with network analysis interpret the results easily. Brief explanations of key indicators (e.g. centrality measures) in the caption could enhance accessibility without overloading the main text.

• The conclusion is slightly repetitive and could be strengthened by more clearly articulating the broader implications of the study. We suggest expanding the section on future work, as there are multiple ways this theoretical and methodological approach could be expanded. For example, applying it to other fields or geographical regions, or performing comparisons across disciplines or even journal types (for example, open access vs. non-open access journals). The conclusion could also highlight how journal editors or stakeholders in academic publishing could benefit from reflecting on their editorial board composition.

• The conclusions could also more explicitly address how findings may inform editorial practices or policy discussions in scholarly publishing, particularly in relation to diversity, inclusion, and governance of editorial boards.

Concluding remarks

We thank the author(s) of the preprint for posting their work openly for feedback. We also thank all participants of the Live Review call for their time and for engaging in the lively discussion that generated this review.

Conflict of Interest

Alan Colin-Arce was a facilitator of this call and one of the organizers. No competing interests were declared by the reviewers.

Competing interests

The authors declare that they have no competing interests.

Use of Artificial Intelligence (AI)

The authors declare that they did not use generative AI to come up with new ideas for their review.