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.
Scanned 9/5/2026
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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`](../../resources/external_tools.md) — tooling to close the gaps reviewers flag
- [`../../resources/official-source-map.md`](../../resources/official-source-map.md) — Language editorial and review-process sources
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