Research Design (lang-research-design)

Language is method-pluralist: it publishes elicited fieldwork, corpus studies, phonetic and experimental work, computational modeling, and diachronic/typological comparison, and it judges each by the standards of its own subfield. The job here is to make the design defensible to a general, possibly cross-subfield, double-anonymous reviewer — and to show the evidence actually supports the theoretical claim from lang-theory-building.

When to trigger

• Choosing or justifying the design before data collection or analysis
• A reader questioned the elicitation, the consultant sample, corpus coverage, measurement, or the typological sample
• Aligning the evidence with the analysis's predictions
• Mixed-evidence work (e.g., corpus + experiment) that must defend each component

Defend the design (by subfield)

Elicited / fieldwork data

• Describe consultant number and background, elicitation method, and the recording/annotation workflow; distinguish elicited judgments from spontaneous/textual data.
• Give data in numbered examples with Leipzig interlinear glossing and a source for each token; a reader must be able to see the pattern, not take it on faith.

Corpus / quantitative usage

• Justify corpus choice, sampling frame, and coding scheme; report inter-annotator agreement for hand-coded variables; state how tokens were extracted and excluded.

Phonetic / experimental

• Specify participants, stimuli, task, and measurement (e.g., forced alignment, formant/pitch extraction settings); pre-empt confounds; where predictions are directional, say so in advance.

Diachronic / typological

• Make sample construction and genealogical/areal control explicit; guard against areal or bibliographic bias; keep a clear trail from primary sources to the coded generalization.

Computational / modeling

• State what the model is a model of; separate the claim about the grammar from the properties of the architecture or training data.

Match design to claim

The single most common Language reviewer objection: the data cannot bear the generalization. Walk the chain: claim → prediction → the observation that would confirm/disconfirm it → the design's leverage on that observation. A three-language convenience sample cannot ground a universal; either narrow the claim or widen the evidence — do not overreach.

Referee-pushback patterns by subfield (the modal Language objection)

Calibration with a quick example (hedged)

Language judges each subfield by its own standard, not a single template; unlike a purely formal venue that accepts introspective judgments alone, it increasingly expects the evidence base to be visible and checkable. Illustrative: an author claims a word-order universal from four related languages; a referee flags "genealogical non-independence." The fix draws a genealogically stratified sample and restates the claim as a statistical tendency with the mechanism, so the typology can see the pattern fail as well as hold. Confirm current data expectations on the author pages and in lang-data-and-transparency.

Design pass for Language

Treat this skill as an executable review pass, not a prose hint. First lock the empirical generalization, evidence base, warrant, and theoretical payoff; then judge whether the manuscript answers the venue's real reader: linguists across subfields who value grounded analysis, transparent and checkable evidence, and careful, appropriately scoped generalizations.

• Do the pass: lock the unit (segment / token / speaker / language), the sample, the comparison, the validity threat, and the minimum decisive evidence before recommending collection or submission.
• Return a ledger: give claim / evidence / risk / manuscript location rows so the next agent can edit rather than rediscover the issue.
• Sibling guard: compare against Phonology, NLLT, Journal of Semantics, Diachronica, Language Variation and Change; if a sibling owns the contribution, recommend re-routing before polishing.
• Stop condition: do not give submission-ready advice until resources/official-source-map.md has been checked and the manuscript has one concrete fix for the largest venue-specific risk.

Anti-patterns

• Grounding a general claim on a convenience sample that cannot support it
• Judgments from a single consultant presented as facts about the language
• Corpus tokens hand-picked with no stated extraction or exclusion rule
• Phonetic effects reported without controlling obvious confounds
• A typological sample with unacknowledged genealogical or areal dependence
• A design that probes something adjacent to, but not, the stated prediction

Output format

【Subfield】fieldwork / corpus / phonetic-experimental / typological-diachronic / computational / mixed
【Claim it must support】from theory-building
【Design leverage】how this evidence bears on the prediction
【Key threats】consultant number, sampling, confounds, non-independence, annotation
【Evidentiary trail】data → glossed examples → claim is legible? [Y/N]
【Verdict】supports the claim / needs tightening / overreaches (fix)
【Next】lang-data-analysis

Supplementary resources

• ../../resources/external_tools.md — elicitation, corpus, and phonetic tooling by subfield
• ../../resources/official-source-map.md — Language method-pluralism and evidence expectations