Transparency & Data Policy (apsr-transparency-and-data-policy)

APSR does not just ask for data — it verifies that the deposited materials reproduce the manuscript's tables and figures before publication. Build the package as you go so conditional acceptance does not stall.

When to trigger

• Building the reproducibility/replication package
• A manuscript reached conditional acceptance and the editorial office requested materials
• Data cannot be fully shared (privacy, ethics, legal/provider restrictions) and you need the

exemption path

• A Replications and Reappraisals submission (materials expectations are central)

What APSR requires (verify current wording on the policy page)

1. Deposit to the APSR Dataverse. Authors of conditionally accepted manuscripts submit a

reproducibility package to the APSR Dataverse on Harvard Dataverse — the journal's dedicated repository with permanent identifiers and preservation. Not a personal website or generic cloud link.

1. Editorial verification. The office reviews the package to confirm it can **reproduce the

manuscript's tables and figures** and that the research process is documented well enough. Treat this as a real check, not a formality.

1. Quantitative materials. Data, code, and documentation sufficient to regenerate every reported

result. Master script + README + pinned versions + seeds.

1. Qualitative materials. Share the materials and data used, alongside literature citations, in a

form that supports the claims (e.g., evidence tables, annotated sources), with access controls where needed (QDR is an option for controlled access).

When data cannot be shared (exemption path)

• Explain why the relevant data are not available (ethical/privacy concerns or legal restrictions

by the data provider).

• Provide README instructions on exactly how others can obtain the data (access process,

application, provider contact).

• Where possible, provide synthetic data resembling the unavailable data so the code can be run.

Build-as-you-go checklist

• [ ] One master script regenerates every table and figure from raw/constructed data
• [ ] README documents data provenance, construction steps, and how to reproduce each exhibit
• [ ] Seeds set and reported for every stochastic step
• [ ] Software/package versions pinned (renv.lock / requirements.txt / recorded installs)
• [ ] Exhibit numbers in the manuscript match the package output exactly
• [ ] Restricted data: exemption note + access instructions + synthetic data where feasible
• [ ] Preregistration / pre-analysis plan linked (anonymized) where applicable

Anti-patterns

• Treating the deposit as a post-publication afterthought (it gates publication)
• Depositing code that does not actually reproduce the printed tables/figures
• A personal URL instead of the APSR Dataverse
• Claiming data are restricted without giving an access path or synthetic substitute
• Undocumented, un-seeded, unpinned code that "works on my machine"

Output format

【Repository】APSR Dataverse (Harvard) — package staged? [Y/N]
【Reproduces tables/figures?】master script verified locally? [Y/N]
【Documentation】README + provenance + seeds + pinned versions? [Y/N]
【Restricted data?】exemption note + access path + synthetic data?
【Qualitative transparency】evidence/sources documented? [Y/N/NA]
【Next】apsr-review-process

Supplementary resources

• ../../resources/external_tools.md — reproducibility tooling and qualitative-transparency options (QDR, ATI)
• ../../resources/official-source-map.md — APSR Research Transparency policy + APSR Dataverse