commres-transparency-and-data
GitHub用于准备传播学研究稿件的透明度、开放科学与可重复性材料。包括撰写数据可用性声明、处理受限数据路径、准备预注册信息及构建复现清单，确保符合SAGE期刊要求。
Trigger Scenarios
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill commres-transparency-and-data -g -y
SKILL.md
Frontmatter
{
"name": "commres-transparency-and-data",
"description": "Use when preparing the transparency, open-science, and reproducibility materials for a Communication Research (CR) manuscript — data-availability statement, deposited data\/code\/materials, preregistration, and the restricted-data path. Prepares the materials; it does not waive requirements."
}
Transparency & Data (commres-transparency-and-data)
CR is a quantitative, social-scientific journal, and its reviewers increasingly expect the materials that let others scrutinize how the numbers were produced. SAGE supports a data-availability statement and open-practices options; build the statement and supporting materials as you write so submission and any open-practice claim go smoothly. Confirm the journal's current wording on the SAGE author page (待核实 on exact policy).
When to trigger
- Drafting the data-availability statement
- Deciding whether to share data, code, and materials, or to preregister
- Preparing a preregistration / pre-analysis plan for a prospective design (note it in the cover letter)
- Data cannot be fully shared (privacy, ethics, platform/legal restrictions) and you need the path forward
What CR / SAGE expects (verify current wording on the policy page)
- Data-availability statement. State where the data are (repository + identifier), under what conditions they can be accessed, and — if they cannot be shared — why, with instructions for how others might obtain them.
- Open practices (where pursued).
- Open data — data and a codebook deposited in a trusted repository with a persistent identifier.
- Open materials — stimuli, instruments, scales, and code deposited so the study can be reproduced.
- Preregistration — a time-stamped, registered design/analysis plan; note it in the cover letter.
- Quantitative materials. Data, code, codebook, scale items, and documentation sufficient to regenerate every reported result; master script + README + pinned versions + seeds.
- ORCID and ethics. Provide ORCID where requested; state IRB/ethics approval and informed consent; for content analysis, deposit the codebook and intercoder-reliability report.
When data cannot be shared (restricted-data path)
- Explain why in the data-availability statement (ethical/privacy concerns, platform terms of service, or legal restrictions by the provider).
- Provide instructions on how others can obtain the data (access process, application, provider contact).
- Where possible, provide synthetic or de-identified data so the code can be run.
Build-as-you-go checklist
- Data-availability statement drafted (repository, identifier, access conditions, or exemption)
- One master script regenerates every table and figure from raw/constructed data
- README documents data provenance, construction, and how to reproduce each exhibit
- Seeds set and reported for every stochastic step; software/package versions pinned
- Scales/stimuli/codebook deposited (open materials) where claimed
- Content analysis: codebook + intercoder-reliability report included
- Materials anonymized (no author-identifying paths/links) for double-anonymized review
Transparency expectations by study type (decision table)
Match the deposit to the design rather than forcing one template:
| Study type | What a CR referee wants deposited | Open practice most relevant |
|---|---|---|
| Experiment | data + codebook + stimuli + analysis script | open data + materials + preregistration |
| Survey / panel | data + scale items + analysis script + measurement model | open data + materials |
| Content analysis | codebook + coder instructions + reliability subsample + texts | open materials (+ open data) |
| Computational / text-as-data | corpus or query, model/version, seeds, human-validation set | open materials + open data |
For computational measures, the human-validation set is itself the evidence that the automated label means what the paper claims — depositing the classifier without it leaves the construct unverified.
Worked micro-example: a DAS for a copyrighted-news corpus (illustrative)
A computational content analysis of 40,000 news articles (illustrative) hits a familiar wall: the texts are copyrighted and the feed bars redistribution. The path: (1) deposit the codebook, article IDs/URLs, query parameters, and analysis code so a same-license reader reproduces the pipeline; (2) deposit the human-validation sample and shareable derived data; (3) write a data-availability statement naming the restriction, provider, and access route, and offering de-identified derived features (frame proportions per article) so modeling re-runs without raw text.
Anti-patterns
- Treating the data-availability statement as an afterthought rather than a submission element
- Claiming an open-practice credit whose materials are not actually deposited or do not reproduce results
- A personal URL instead of a trusted repository with a persistent identifier
- Claiming data are restricted without giving an access path or synthetic substitute
- De-anonymizing the manuscript via an open-materials link during review
Output format
【Data-availability statement】drafted? repository + identifier or exemption? [Y/N]
【Reproduces tables/figures?】master script verified locally? [Y/N]
【Open practices sought】open data / open materials / preregistration (materials staged?)
【Documentation】README + provenance + seeds + pinned versions? [Y/N]
【Restricted data?】exemption note + access path + synthetic data?
【Ethics/ORCID】IRB + consent stated; ORCID provided? [Y/N]
【Next】commres-review-process
Supplementary resources
../../resources/external_tools.md— reproducibility tooling and repositories (OSF, Dataverse, QDR)../../resources/code/— master-script + seed-discipline skeleton../../resources/official-source-map.md— data-availability and open-practices policy
Version History
- 1839142 Current 2026-07-05 12:38
