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spq-data-and-transparency

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Use when preparing the data, materials, and transparency posture for a Social Psychology Quarterly (SPQ) manuscript. SPQ ENCOURAGES sharing data, code, and materials but does NOT require it, and willingness to share has no impact on acceptance; the journal follows the ASA data-sharing norm and Code of Ethics. Covers quantitative and qualitative/interpretive transparency and confidentiality. Prepares the posture; it does not invent requirements.

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Source SKILL.md: https://github.com/brycewang-stanford/Awesome-Journal-Skills/blob/HEAD/Social-Psychology-Quarterly-Skills/skills/spq-data-and-transparency/SKILL.md

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Data & Transparency (spq-data-and-transparency)

SPQ's posture is deliberately different from open-data-mandate journals. It encourages researchers to make data, code, and materials available, but this is not a requirement, and willingness to publicly release data and materials has no impact on the likelihood of acceptance. The journal recognizes that not all areas of social psychology — especially ethnographic and interview work — can share data practically or ethically. Transparency at SPQ means clear documentation and honoring the ASA data-sharing norm, not a verified replication gate.

When to trigger

  • Deciding what data/code/materials to share, and how to describe your transparency posture
  • Confidential or sensitive data (fieldnotes, interview transcripts, restricted survey data)
  • A reviewer asked about materials, measures, or replicability
  • Writing the data-availability and ethics language

What SPQ actually asks (verify current wording on the policy page)

  1. Encouraged, not required. SPQ encourages open data, code, and materials so others can review and use them — but does not require it, and non-sharing does not lower acceptance odds. Do not write as if it were a gate; do not over-claim "open" materials you cannot release.
  2. ASA data-sharing norm. As a regular practice, sociologists share data and documentation as part of a research plan and generally make data available after a project's completion or major publications, except where proprietary agreements preclude it or where confidentiality of participants cannot otherwise be protected (e.g., fieldnotes, detailed ethnographic interviews).
  3. Quantitative materials (if shared). Data, code, and documentation sufficient to regenerate reported results: master script + README + pinned versions + seeds + scale items.
  4. Qualitative / interpretive transparency. You generally cannot share raw fieldnotes or interview transcripts; instead document the analytic process — sampling/site logic, coding scheme, and enough excerpts for readers to judge — and protect participant confidentiality.

Confidentiality & ethics

  • Protect participants: de-identify, aggregate, or withhold where re-identification is a risk.
  • Honor IRB/consent terms and any data-provider restrictions; say so plainly if data cannot be shared.
  • Submitting the same manuscript elsewhere while under SPQ review is unethical; flag prior appearance of significant findings.

Good-practice checklist (not a mandate)

  • Decide and state a clear, honest data-availability posture (what you can/can't share and why)
  • If sharing quantitative materials: master script regenerates tables/figures; README; seeds; pinned versions
  • If interpretive: document sampling/site logic and coding; provide representative excerpts; protect confidentiality
  • Scale items / measures documented (in text or supplementary materials)
  • Ethics/IRB and confidentiality handled per ASA Code of Ethics
  • Preregistration linked (anonymized) where you used it — useful but not required

Anti-patterns

  • Writing as though SPQ mandates open data, or implying sharing buys acceptance (it does not)
  • Claiming data are "available" when consent/confidentiality actually preclude release
  • No documentation of measures or analytic procedure at all
  • Exposing participant identities to perform "transparency"
  • Treating qualitative transparency as impossible and so documenting nothing

Output format

【Posture】what data/code/materials will (or will not) be shared, and why
【Encouraged-not-required understood?】[Y/N]
【Quantitative (if shared)】master script + README + seeds + measures? [Y/N/NA]
【Qualitative transparency】sampling/coding documented + confidentiality protected? [Y/N/NA]
【Ethics/IRB + ASA norm honored】[Y/N]
【Next】spq-review-process

Supplementary resources