lang-review-process
GitHub用于预判《Language》期刊稿件的评审流程与拒稿风险。通过模拟双盲审稿标准，检查理论主张、跨框架对话及数据透明度，帮助作者在提交前识别描述性堆砌等陷阱，校准预期并优化稿件质量。
Trigger Scenarios
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill lang-review-process -g -y
SKILL.md
Frontmatter
{
"name": "lang-review-process",
"description": "Use when anticipating how a Language (LSA) manuscript will be judged — the double-anonymous review, the general-audience and cross-framework bar, the desk-return filters (descriptive data dump, single-framework parochialism, undocumented data), and the decision categories. Sets expectations and stress-tests before submission; it does not write the paper."
}
Review Process (lang-review-process)
Knowing how Language actually evaluates a manuscript lets you pre-empt the objections before you submit. Language runs double-anonymous review under co-editors and an editorial team, drawing referees from across subfields, and it screens hard at intake: a paper that is a descriptive data dump, that lives inside one framework, or that rests on undocumented data may be returned before external review. This skill maps the process and stress-tests the paper against it.
When to trigger
- Before submission, to predict reviewer objections and the likely outcome
- After a decision letter, to read the outcome category correctly (then route to
lang-rebuttal) - Deciding whether the piece fits a full article or a shorter/online section
- Calibrating expectations for a first-round outcome
What the process looks like (verify on the author pages)
- Intake screen. Editors check fit, section, anonymization, and whether the paper makes a theoretically grounded claim for a general audience. Data dumps and framework-internal exercises can be returned without review.
- Double-anonymous external review. Referees from the relevant subfields — and often one from outside it — assess the generalization, the analysis, the evidence, engagement across frameworks, and the transparency of data and glossing.
- Decision. Typical categories: accept (rare on first pass), minor revisions, major revisions / revise-and-resubmit, reject. A substantive R&R is the normal good outcome.
- Perspectives track. A Perspectives target article is reviewed, then paired with invited Commentaries and an author Rejoinder — a different rhythm from the standard article.
What reviewers are asked to weigh (anticipate each)
| Reviewer question | Pre-empt it with… |
|---|---|
| Is there a real theoretical claim, not just description? | lang-theory-building — state the general claim + predictions |
| Does it engage rival frameworks fairly? | lang-literature-positioning — adjudicate, don't ignore |
| Can the data bear the generalization? | lang-research-design — scope the claim to the evidence |
| Are the statistics appropriate? | lang-data-analysis — mixed-effects, effect sizes, no pseudoreplication |
| Can I check the data and glosses? | lang-data-and-transparency — share data/code, source glosses |
| Is it readable outside the subfield? | lang-writing-style — theory-neutral statement, glossed jargon |
Desk-return filters (the intake traps)
| Intake trap | Why it triggers a return | Fix before submitting |
|---|---|---|
| Descriptive data dump | no theoretical stakes | frame what the data are a case of |
| Single-framework parochialism | ignores rival analyses | make the adjudicating prediction explicit |
| Undocumented data | reviewers cannot check it | source glosses; share analysis data/code |
| Wrong venue | belongs at a subfield journal | re-route, or broaden the claim |
| Anonymization break | double-anonymous integrity | strip identifiers and metadata |
Calibration (Language review culture, hedged)
Orienting heuristics, not guarantees; confirm process details on the current author pages. Language review rewards a grounded, framework-fluent, checkable paper and is patient with careful revision: the realistic first-round outcome for a promising submission is a major revision, not acceptance, and the revision often asks you to broaden the framework engagement or firm up the statistics. Illustrative: a phonetics paper returns with "revise and resubmit — strengthen the model and engage the exemplar-theoretic alternative"; the productive response refits a mixed-effects model, adds the rival's prediction and tests it, and documents the measurement pipeline, rather than defending the original as-is.
Anti-patterns
- Submitting without pre-empting the obvious cross-framework objection
- Reading a major-revision letter as a rejection (or a rejection as negotiable)
- Assuming a subfield-journal analysis will clear the general-audience bar unchanged
- Ignoring the intake filters and getting returned before review
- Treating a Perspectives Commentary like a standard referee report
Output format
【Predicted intake risk】data-dump / parochial / undocumented / wrong-venue / anon-break / none
【Top reviewer objections】the 2–3 most likely, with the pre-empting skill
【Likely first-round outcome】accept / minor / major-R&R / reject (hedged)
【Section fit】full article / research report / online section / Perspectives
【Action】fixes to make before submission
【Next】lang-submission (pre-decision) or lang-rebuttal (post-decision)
Supplementary resources
../../resources/external_tools.md— tooling to close the gaps reviewers flag../../resources/official-source-map.md— Language editorial and review-process sources
Version History
- 9f86f09 Current 2026-07-19 16:57
