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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