| name | methodology-selection |
| description | Use this skill whenever a user needs help selecting, justifying, or evaluating research methods for anthropological or qualitative research. Triggers include: "which methods should I use," "how do I justify my methods," "method-stance alignment," "my reviewer says my methods don't match my theory," "multi-method design," "mixed methods in anthropology," or "what methods fit an interpretivist / critical / STS / feminist / applied project." Also trigger on questions about epistemic coherence between theory and methods, evidence types needed for a research question, composing a multi-method system, writing a methods justification narrative, or data governance as a design decision. Do NOT use for writing a full research plan (use research-plan skill), grant proposals targeting a specific funder (use grant-proposal skill), or designing specific instruments like interview guides (use fieldwork-methods skill). This skill handles the upstream design decision of which methods and why.
|
Methodology Selection
Select and justify research methods for anthropological research by treating
method choice as an epistemic-design problem: specifying a warranted path
from an epistemic stance and research question to defensible claims, using
evidence types the stance treats as meaningful, through a coherent
multi-method system whose internal logic is explicit. Method selection is
not "picking tools" — it is an argument about why these methods, for this
question, from this stance, will produce the evidence needed to support
the claims you intend to make.
Quick Reference
Workflow
Step 1: Identify What the User Needs
Determine the entry point:
- Selecting methods from scratch. The user has a research question and
stance but hasn't chosen methods yet. Load the guide and run the full
decision workflow.
- Justifying existing choices. The user already has methods but needs
help writing a defensible justification narrative. Load the compatibility
map for stance-specific templates and the guide for phrasing patterns.
- Checking stance-method coherence. The user wants to know if their
proposed methods fit their epistemic stance (often prompted by reviewer
feedback). Load the compatibility map to check S/C/I/T ratings.
- Writing a methods justification narrative. The user needs proposal-ready
or paper-ready prose explaining their method system. Load the compatibility
map for stance-family templates and the guide for phrasing patterns.
Step 2: Gather Context
Before generating any content, collect these inputs:
Required:
- Research question(s). What is the user trying to answer? This
determines what evidence is needed.
- Epistemic stance. Which theoretical orientation(s) does the researcher
work within? Ask for primary and secondary. The stance determines what
counts as evidence and what methods are epistemically coherent.
- Field configuration. Single site, multi-sited, digital, archival,
hybrid? This constrains which methods are practical.
Important but can be inferred:
4. Scale and temporality. Small-N intensive, multi-population, longitudinal,
cross-sectional? Affects the design logic.
5. Access constraints. Where observation is impossible or risky, trace and
documentary methods become more central; where recruitment is constrained,
sampling logic must shift.
6. Risk posture. Low-risk, vulnerable populations, high-surveillance,
politically sensitive. Affects ethics and data governance requirements.
7. Resources, skills, time. Methods that cannot be implemented with rigor
are not "best" methods. Short timelines may favor rapid assessment.
Helpful but not required:
- Downstream target: will this feed into a proposal, research plan, or paper?
- Career stage (affects ambition calibration)
- Language competencies
- Whether methods have already been partially chosen
Step 3: Load Appropriate References
- Always load
references/methodology-selection-guide.md for the
decision workflow, criteria, and checklist.
- Load
references/method-stance-compatibility.md when the user needs
stance-specific guidance: compatibility ratings, justification templates,
or worked examples.
- Load
references/method-modules.md when comparing method options or
composing a multi-method system: evidence types, claims supported,
limitations, ethical considerations, and multi-method design patterns.
Step 4: Run the Decision Workflow
Follow this sequence (detailed in the guide reference file):
-
Define the claim envelope. Based on the epistemic stance, state what
kinds of claims are admissible and what kinds are not. An interpretivist
project makes claims about meaning, not prevalence. A critical project
makes claims about power, not neutral description.
-
Decompose the question into evidence needs. Translate the research
question into required evidence types: embodied practices (requires
observation), meaning-making (requires interpretive elicitation plus
context), distributions (requires standardized measurement), discourse-in-use
(requires recordings and transcription), historical sequence (requires
archives), network/process across sites (requires multi-sited or trace
strategies), materiality (requires object-oriented or sensory methods).
-
Generate candidate method modules. From the 14 method modules in the
method-modules reference, identify which could produce the required evidence.
-
Check epistemic coherence. Using the compatibility matrix, rate each
candidate method against the user's stance: Standard (S), Coherent (C),
Innovative/defensible (I), or High-tension (T). Flag any T-rated methods
and explain what reframing would be needed to make them defensible.
-
Check field constraints. Filter candidates by access, risk, consent
feasibility, platform terms, legality, and resource availability.
-
Compose the multi-method system. Assign each surviving method a role:
primary evidence generation, complementary perspective, contextualization,
or validation. Ensure the system has internal logic — methods should relate
to each other, not just coexist.
-
Specify the integration plan. State when and where evidence streams
are joined, what analytic strategy governs integration, and what
meta-inferences result. Do not use "triangulation" without specifying
the type (data, method, theory) and what convergence or divergence means.
Step 5: Generate Output
Produce one or more of these deliverables depending on user needs:
- Method justification narrative. Stance-grounded prose explaining the
method system. Use the stance-family templates from the compatibility
reference. Every method gets a role statement: what evidence it produces,
what claims it supports, what its limitations are.
- Method-system composition. A structured overview of the method system
showing each module, its role, its evidence contribution, and how it
integrates with other modules.
- Integration plan. When and how evidence streams are combined, what
analytic strategy governs integration, and what meta-inferences result.
- Ethics and data governance plan. Consent strategy, identifiability
analysis, storage and embargo choices, platform-specific ethics for digital
methods, and rules for future sharing.
Step 6: Quality Check
Before presenting output, verify using the full checklist:
Parameters
- Epistemic stance: All 42 stances are relevant, grouped into stance
families for compatibility mapping (interpretive/hermeneutic,
phenomenological, critical/political economy, feminist/queer, STS/ANT,
applied/design, cognitive/psychological, linguistic, computational/digital,
plus an unspecified-family template). See DESIGN.md for the full list.
- Genre/audience: Methods section (for proposal, plan, or paper),
standalone methodology design memo, methods justification narrative.
- Compression: Brief design sketch (1-2 paragraphs), methods rationale
(1-2 pages), full methods section (3-8 pages).
- Risk posture: Low-risk, vulnerable populations, high-surveillance,
politically sensitive. Higher risk postures require more detailed ethics
and data governance.
- Field configuration: Single site, multi-sited, digital, archival,
hybrid, comparative.
- Scale: Small-N intensive, multi-population, longitudinal,
cross-sectional.
Guardrails
- Do not generate without knowing the epistemic stance. Stance determines
what counts as evidence, what methods are coherent, and what claims are
admissible. "Methods" without a stance is an incoherent request — ask
the user to identify their stance before proceeding.
- Do not produce methods as a grocery list. Every method must have a
role statement: what evidence it produces, what claim it supports, what
its limitation is. "I will use participant observation, interviews, and
surveys" is a failure mode unless each method's contribution is specified.
- Do not claim triangulation without specification. Require the type of
triangulation (data, method, theory) and state what convergence or
divergence would mean for inference. "Triangulation" as a magic word is
a documented failure mode.
- Flag stance-method tension explicitly. When a proposed method is rated
High-tension (T) for the user's stance in the compatibility matrix,
explain the tension and what reframing would be needed. Do not silently
pass high-tension combinations.
- Ethics and data governance are design determinants. Do not treat them
as an appendix. Risk, identifiability, consent feasibility, and future
harms from data circulation must inform method selection, not just
accompany it.
- Require validation for computational methods. If computational text
analysis, network analysis, or other automated methods are included,
require a validation plan (close reading, triangulation, error analysis).
Model outputs are not self-validating.
- Require internet-specific ethics for digital methods. If digital
ethnography, trace methods, or platform-based research is included,
require explicit treatment of public/private ambiguity, searchability
of identifiers, platform terms, and consent expectations.
Common Failure Modes
| Failure mode | Prevention |
|---|
| Methods as grocery list — no inferential role specified | Require a role statement per method: evidence -> claim -> limitation |
| Generic justification — "participant observation is a hallmark of anthropology" | Enforce stance-and-question anchoring: why this method is necessary here |
| Stance-method mismatch hidden by vague language | Add claim envelope step; check compatibility matrix; flag T-rated methods |
| Integration left implicit — "triangulation" as magic word | Specify type of triangulation and what convergence/divergence means |
| Sample size by round number or unexamined "saturation" | Use information power or empirically grounded saturation reasoning |
| Ethics treated as appendix | Require ethics and data governance as design determinants, not afterthoughts |
Examples
Example 1: Selecting methods for an interpretivist project
Input: "I'm studying how gig workers make meaning out of algorithmic
management. I'm an interpretivist drawing on practice theory. What methods
should I use?"
Output approach:
- Load all three reference files
- Set epistemic stance to interpretivist + practice theory
- Claim envelope: meaning-making, practice-account relations, situated
explanation — not prevalence or causal measurement
- Evidence needs: embodied practices (observation), interpretive frames
(interviews), institutional categories (documents)
- Method system: participant observation (ride-alongs, waiting spaces) +
semi-structured interviews + document analysis (platform communications,
worker forums as texts) — all S or C rated for interpretive stance
- Integration: observation builds domain knowledge and refines interview
guides; interviews test interpretive hypotheses; documents trace category
circulation; iterative qualitative analysis across all streams
- Role statements for each method
Example 2: Selecting methods for a computational/digital project
Input: "I want to study how climate misinformation spreads in online
communities. I'm coming from a computational/digital ethnography perspective.
I'm thinking of scraping forum data and doing topic modeling."
Output approach:
- Load all three reference files
- Set epistemic stance to computational/digital
- Claim envelope: pattern identification at scale, platform-mediated practices,
distributed coordination
- Check forum scraping + topic modeling: both S-rated for computational/digital
stance, but require validation plan
- Recommend adding digital ethnography (community engagement, contextual
interpretation) to ground computational findings — S-rated, standard
integration pattern
- Require: validation through close reading, participant engagement for
interpretation, internet-specific ethics (consent, searchability,
platform terms)
- Flag: scraping without ethical governance plan is a guardrail violation
Example 3: Checking stance-method coherence
Input: "I'm doing a feminist study of reproductive healthcare access but my
advisor wants me to include a survey. Is that compatible with my framework?"
Output approach:
- Load compatibility reference
- Check surveys against feminist/queer stance: rated C (coherent, not
standard) — epistemically compatible but requires explicit framing
- Explain: surveys are coherent within feminist frames when they
operationalize structural exposure (access barriers, wait times,
insurance status) and are integrated with ethnographic interpretation,
not used as standalone "proof"
- Recommend framing: position survey as mapping the distribution of
structural barriers that ethnography then explains in terms of lived
experience and power; include critical analysis of what the survey
categories make visible and invisible
- Flag: surveys become high-tension if treated as neutral measurement
without feminist critique of the categories themselves