Humrel methods
Skill brycewang-stanford/Awesome-Journal-Skills/Human-Relations-Skills/skills/humrel-methods
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Use when choosing and justifying the research design for a Human Relations (HR) manuscript — qualitative/ethnographic, critical, quantitative, or mixed — and setting the rigor bar. Designs the study; it does not run the analysis (see humrel-data-analysis).
SKILL.md
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Methods & Research Design (humrel-methods)
When to trigger
- You are choosing among a qualitative/ethnographic, critical, quantitative, or mixed-methods design
- The design is chosen but its rigor and transparency are not yet defensible
- A qualitative study lacks a sampling logic or trustworthiness safeguards
- A quantitative study lacks construct validity or theorizes only the coefficient
- A mixed-methods study cannot say why both strands and what each adds
Principle: method follows the theoretical question — and HR privileges none
HR treats qualitative, critical, quantitative, and mixed-methods work as equally first-class, in the Tavistock human-relations tradition. There is no house preference for an estimator or a paradigm; what is non-negotiable is that the design fits the social-theoretical question (from humrel-theory-development) and is executed with rigor, transparency, and reflexivity. A sophisticated method cannot rescue a thin theory, and a single immersive ethnography can carry an HR paper if the insight is deep and the craft is high. Note also the double-anonymous review: write methods so they establish credibility without revealing the authors' institution, field site identity, or grant.
Branch A — Qualitative / ethnographic design
For how/why process, meaning, identity, and contested dynamics at work.
- Theoretical (not convenience) sampling. Sites/cases/informants chosen to illuminate the mechanism; state the logic (polar types, extreme/critical case, longitudinal, theoretical replication).
- Access and immersion. Specify duration, depth, and your role (participant vs. non-participant); for ethnography, time in the field; for historical work, the archive.
- Triangulated data. Interviews (count, who, when, guide), observation, documents — and how they corroborate.
- Trustworthiness. Credibility, transferability, dependability, confirmability: member checks, prolonged engagement, audit trail, negative-case analysis.
- Reflexivity. State your standpoint and how it shaped access, interpretation, and the relations you studied — HR expects this, not as confession but as method.
Branch B — Critical design
For research interrogating power, ideology, discourse, and taken-for-granted arrangements.
- Make the critical-theoretical lens explicit (labour process, Foucauldian, feminist, postcolonial, CDA) and tie analytic choices to it.
- Treat reflexivity and positionality as central, not optional.
- Ensure the critique is generative: the design must surface a constructive theoretical claim, not only an unmasking.
Branch C — Quantitative design
For whether/how much/under what conditions across many cases.
- Sample and unit of analysis justified relative to the theory (individuals nested in teams/organizations; dyads; events).
- Construct validity. Operationalizations defended; multi-item measures with reliability; address common-method bias if same-source/cross-sectional.
- Multilevel structure. If theory is cross-level, use HLM/mixed models and justify aggregation.
- Identification in service of theory. Where causal claims are made, state the threat and the strategy (panel FE, longitudinal lags, quasi-experiment) — but identification is a means to a theoretical end at HR, not the contribution itself.
Branch D — Mixed methods
- State the integration logic: sequential, concurrent, or nested, and what each strand adds that the other cannot. Avoid bolting a few interviews onto a survey for decoration.
Either branch
- The design must let you see the mechanism, not just endpoints.
- Pre-empt obvious alternative explanations at the design stage.
- Plan the data-to-theory link now (feeds
humrel-data-analysisandhumrel-tables-figures).
Execution bridge (StatsPAI / Stata MCP)
For the empirical / causal lane, estimate and audit rather than only specify. Full
map: execution-with-mcp. Human Relations blends critical/qualitative and quantitative work; apply the chain below to its survey / experimental quantitative papers.
detect_design→recommend→ fit withas_handle=true→audit_resultto enumerate the checks the design owes.- Panel / staggered DiD:
callaway_santanna/sun_abraham+bacon_decompositionhonest_did_from_result. IV:effective_f_test+anderson_rubin_ci. RDD:rdrobust+mccrary_test.
- Experiments: randomization-based inference and
romano_wolffor the many-outcome family-wise correction reviewers expect.
Match the toolchain to the reviewer pool, and report the effect size the venue wants. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.
Checklist
- Design matches the theoretical form (process → qual/critical; variance → quant)
- Qual: theoretical sampling stated; access/immersion specified; trustworthiness named
- Critical: lens explicit; reflexivity central; critique is generative
- Quant: construct validity and (if needed) multilevel structure addressed
- Mixed: integration logic and the added value of each strand stated
- Obvious alternatives are designed against, not just discussed later
- Methods text is anonymized (no institution/site/grant tells)
Anti-patterns
- Convenience sampling dressed up as theoretical sampling
- Qualitative work with no transparency about coding, sources, or fieldwork depth
- A fancy estimator chosen to signal rigor when the question doesn't need it
- Critical work that is reflexive in tone but methodologically opaque
- "Mixed methods" that is a survey with ornamental quotes
- Methods that reveal author/site identity in a double-anonymous submission
Output format
【Journal】Human Relations
【Skill】humrel-methods
【Design】qualitative / critical / quantitative / mixed (type)
【Why it fits】link to the social-theoretical question
【Sampling/identification】logic + key threat addressed
【Rigor safeguards】trustworthiness / construct validity / integration logic
【Anonymization】no site/institution/grant tells (yes/no)
【Next skill】humrel-data-analysis