lang-data-and-transparency
GitHub协助准备语言学稿件的数据、注释及可复现材料，涵盖共享数据集、音档及伦理考量。指导如何根据数据类型（定量、田野、语音）透明地文档化和分享数据，确保符合期刊规范并尊重社区协议，避免过度或不足声明。
Trigger Scenarios
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill lang-data-and-transparency -g -y
SKILL.md
Frontmatter
{
"name": "lang-data-and-transparency",
"description": "Use when preparing the data, annotation, and reproducibility materials for a Language (LSA) manuscript — shared datasets and code, glossed corpora, sound files, and the ethics of working with language consultants and communities. Language values transparent, documented data; over-stating a mandated deposit is as wrong as hiding materials. Documents and shares; it does not run the analysis."
}
Data & Transparency (lang-data-and-transparency)
Language increasingly treats documented, checkable data and reproducible analysis as a mark of serious work: a reader should be able to see the pattern and, where quantitative, re-run the model. But the requirements differ by subfield and evolve, and linguistic data carry ethical obligations to consultants and communities that generic "open data" rhetoric ignores. This skill helps you document, share, and protect your materials appropriately — without over-stating a deposit mandate the journal may not impose.
When to trigger
- Assembling the data/code/annotation to accompany a submission
- Deciding what can and cannot be shared (consultant confidentiality, community agreements, licensed corpora)
- A reader asked for the dataset, the glossed corpus, the sound files, or the analysis script
- Writing a data-availability statement
What "transparent" means at Language (by data type)
Quantitative (experiment / corpus)
- Share the analysis-ready data and the script that reproduces the models, tables, and figures; pin package versions and set seeds. A repository (e.g., OSF) with a readme is the norm.
- If the raw corpus is licensed, share the derived counts + the extraction code so the pipeline is reproducible even when the source text cannot be redistributed.
Elicited / fieldwork
- Provide numbered, Leipzig-glossed examples with sources; where possible, archive recordings and annotations in a language archive (e.g., ELAR, PARADISEC, AILLA, TLA) under access terms the community agreed to.
- Document the elicitation and transcription workflow so another linguist could interpret the data.
Phonetic
- Share measurement scripts (e.g., Praat scripts) and, where consent allows, the sound files or acoustic measurements; state the alignment/measurement settings.
Ethics of linguistic data (do not skip)
- Consent and community agreements govern what may be archived and how; open sharing is not always ethical, and "restricted access" is a legitimate, respectful choice.
- Anonymize speakers where required; do not expose identities via metadata or audio.
- Credit consultants and communities per current best practice and any community protocol.
Calibration (do not over- or under-state, hedged)
Language rewards transparency as craft, but the pack does not assert a specific editor-verified replication mandate — verify the current data-availability policy on the CUP/LSA author pages before claiming any gate. The honest posture: share what you ethically can, document what you cannot, and never present restricted community data as if it were freely open. Illustrative: a variationist study shares the coded token file, the R script, and a codebook on OSF, but keeps the raw interview audio restricted under the community agreement and says so in the data statement — transparent and ethical at once.
Referee/editor conformance check
| Slip reviewers catch | The Language-appropriate fix |
|---|---|
| "Results not reproducible from what's shared." | post analysis data + script; pin versions, set seeds |
| "Glosses can't be checked." | numbered Leipzig-glossed examples with per-token sources |
| "Licensed corpus can't be shared." | share derived counts + extraction code + a pointer to the source |
| "Speaker identities exposed." | anonymize; restrict audio per consent |
| "Claims a deposit rule that isn't stated." | describe your sharing; verify the live policy, don't invent one |
Anti-patterns
- Quantitative results with no shared data or script (reviewers cannot reproduce the model)
- Treating community/consultant data as "open" without consent or agreement
- Exposing speaker identities through metadata, audio, or examples
- Glossed data with no source, so a reader cannot verify the token
- Over-stating a journal replication mandate the live policy does not impose (verify first)
Transparency pass for Language
Treat this skill as an executable review pass, not a prose hint. First lock what evidence underlies each claim; then judge whether the manuscript answers the venue's real reader: linguists who value checkable evidence and who also respect the ethics of working with speakers and communities.
- Do the pass: for each claim, name where the supporting data and code live, the access terms, and any ethical constraint on sharing.
- Return a ledger: give
claim / evidence / where-it-lives / sharing-constraintrows so the next agent can act. - Sibling guard: documentation-heavy work may fit Language Documentation & Conservation; if a sibling owns the contribution, recommend re-routing before polishing.
- Stop condition: do not give submission-ready advice until
resources/official-source-map.mdhas been checked for the current data-availability policy.
Output format
【Data types】experiment / corpus / elicited / phonetic / archival
【Shared】analysis data + script posted (repo/OSF)? [Y/N/NA]
【Glossed examples】numbered, Leipzig, sourced? [Y/N]
【Ethics】consent / community agreement / anonymization handled? [Y/N]
【Data statement】accurate, no over-stated mandate? [Y/N]
【Next】lang-tables-figures
Supplementary resources
../../resources/external_tools.md— archives, OSF, glossing and reproducibility tooling../../resources/official-source-map.md— Language data-availability policy live-check
Version History
- 9f86f09 Current 2026-07-19 16:57
