Manuscripts submitted to IO should make it easy for peer reviewers to understand exactly how the research was conducted and the key choices the researchers made in designing the research.  Both quantitative and qualitative papers should justify case selection and explain how data were collected.  All submissions reporting the results of surveys, survey experiments and/or other forms of experiments should include all relevant survey instruments (or, for large surveys, all relevant portions of survey instruments) and experimental protocols. Authors may opt to include these in the main text or as part of supplemental materials.  

We also expect authors to follow the recommendations on survey research disclosure developed at the 2021 National Academy of Sciences retreat, and summarized in this 2023 statement. These include (a) disclosure of  sampling design, modeling and weighting assumptions for all surveys—probability and non-probability alike; (b) disclosure of question wording and order; (c) discussion of respondent recruitment and question-related panel conditioning factors; (d) disclosure of known and expected consequences of attrition for panel surveys; (e) when survey data are weighted, the phrase “representative sample” should not be used without explicit acknowledgment of the underlying assumptions, including disclosure of weighting and modeling used.

Authors of papers including formal models must provide complete proofs at the time of initial submission, which also may be included in supplemental materials. While the general limit for supplemental materials is 20 pages, the editors will accept longer supplemental materials if this is necessary to provide a full survey instrument, experimental protocol, or formal proof.  

Prior to final acceptance, results of papers using quantitative data and proofs of formal models will be verified by IO staff. Authors of papers using quantitative data must provide the data and accompanying command files to reproduce tables presented in the paper and support any other claims made based on analysis of data (for example, results verbally described in the main text or in footnotes). The editorial staff will request data at the time of conditional acceptance; authors do not need to provide data or command files upon initial submission. The editors will not issue final acceptances until all results of all reported analyses are confirmed.

For authors using qualitative evidence, we strongly encourage transparency about the research process as well as the data collected. We note that, even when concerns about protecting human participants might raise concerns about, for instance, sharing archival materials or interview notes, authors can provide details on how a study was conducted – how interviewees were selected; which archives were consulted; or what questions were asked of research participants. This Kapiszewski and Karcher article (2021) offers some helpful guidelines for making qualitative research more transparent.

We also encourage authors using qualitative evidence to consider depositing their data at Syracuse University’s Qualitative Data Repository (QDR). The QDR provides detailed guidance on how to maintain confidentiality and protect human participants in research, while also preparing qualitative data for sharing. Authors who want to create a QDR file for their project should initiate this process early, so that the DOI for the file can be included in the IO article text. Authors using archival resources also should consider using Annotation for Transparent Inquiry (ATI). Here are two examples of IO articles using ATI: 

Musgrave, Paul, and Daniel H. Nexon. 2018. “Defending Hierarchy from the Moon to the Indian Ocean: Symbolic Capital and Political Dominance in Early Modern China and the Cold War.”

O’Mahoney, Joseph. 2017. “Making the Real: Rhetorical Adduction and the Bangladesh Liberation War.”

IO Dataverse

Upon final acceptance, authors should upload quantitative data sets and supporting files to the IO Dataverse. The Dataverse entry should include the article title and abstract; Dataverse will provide a DOI (a permanent identifier) for the entry, which should be included in the published article. 

Data Availability Statement 

We require a Data Availability Statement for all articles that employ quantitative data (referencing the IO Dataverse), and we encourage a Data Availability Statement for articles that employ qualitative data. The Data Availability Statement appears at the end of the article, before the reference list. 

Guidance on how to write a Data Availability Statement can be found here. Please try to provide clear information on where the data associated with you research can be found and avoid statements such as “Data available on request”. A list of other suggested data repositories can be found here.