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Doctoral Methodology Justification and Rigour
Defend every method choice against the alternatives you rejected, and evidence rigour with practices and artefacts rather than vocabulary.
Free. Works on Claude, ChatGPT, Gemini or any assistant that accepts a skill file.
What this skill does
The method, encoded.
The difference between a masters methodology chapter and a doctoral one is not length or technical difficulty. A masters chapter describes what was done. A doctoral chapter argues why this and not that: what the rejected alternatives would have bought, what the chosen design costs, and what that cost does to the conclusions.
This skill builds that argument. It derives design requirements from each research question separately, which routinely exposes a question the chosen design cannot answer. It builds a comparative table for every major choice, including the alternative an expert examiner would most plausibly have picked, and categorises each rejection honestly as validity, feasibility, ethics, access or paradigm fit, because a feasibility rejection dressed as a principled one is exactly what an examiner exposes.
It tests philosophical coherence in both directions: does the declared position imply these methods, and would the methods as actually practised imply a different position? It instantiates every validity threat against the specific study rather than listing textbook categories. For qualitative work it replaces trustworthiness vocabulary with the practices behind it: a real audit trail, negative case analysis, appropriate member checking, thick description, and reflexivity that is analytic rather than confessional.
It also handles the claims examiners test hardest: sampling stopping rules, saturation evidenced rather than asserted, instrument validation populations, what the pilot actually changed, and every deviation from plan.
Best used for
- Converting a descriptive methodology chapter into a defended argument
- Testing whether a declared paradigm and the chosen methods cohere
- Replacing asserted trustworthiness vocabulary with evidenced practice
- Defending sampling decisions and saturation claims
- Preparing the methodology chapter for expert examination
Typical inputs
What you give it.
Final research questions, The design as actually executed, including departures from plan, The candidate's own statement of their philosophical position, Alternatives considered and rejected, with dates, Pilot materials and results, Instruments and any validation evidence, Memos, coding records, field notes and reflexive journal, Disciplinary expectations on pre-registration and data sharing
Typical outputs
What you get back.
Design requirements table derived per research question, Comparative justification tables with categorised rejection reasons, Forward and backward philosophical coherence check, Validity threat register with instantiation, treatment and affected claims, Rigour practices table mapping criteria to artefacts and locations, Analytic reflexivity statement with consequences and actions, Sampling justification with a stopping rule stated in advance and evidenced, Instrument validity argument including validation population and adaptations, Pilot report of what changed, Transparency and availability statement, and a complete deviation log, Limitations derived from the study's own decisions
Method coverage
What the skill works through.
- Why comparative justification is what makes a chapter doctoral
- Deriving design requirements from each research question
- Naming the alternatives you rejected and why
- Testing whether your philosophy and your methods actually cohere
- Validity threats instantiated rather than listed
- Qualitative rigour as practices and artefacts, not vocabulary
- Reflexivity that is analytic rather than confessional
- Sampling logic and stating a stopping rule in advance
- Instrument validation and what adaptation breaks
- What the pilot changed
- Transparency, reproducibility and pre-registration
- Turning weaknesses into limitations with consequences
- Academic integrity and AI use
Download
Free skill. One file.
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How to install
Add the skill file and the five kernel protocols to a Claude Project, a ChatGPT Project, a Gemini Gem, or paste them at the top of any assistant conversation. Then give it your real research material, not a description of it.
Download skillQuestions
Common questions.
How do I justify my choice of research method?
Comparatively. State what the research question required of a design, list the genuine alternatives including the one an expert would most plausibly have chosen, and for each say what it would have delivered, what it would have cost, and why it was rejected. Categorise the rejection reason honestly: validity, feasibility, ethics, access or fit with your paradigm. Then state what your chosen design costs and what that cost does to your conclusions.
How do I know if my epistemology matches my methods?
Check in both directions. Forwards: does your declared position imply these methods, or would it equally imply several others, in which case the position is decorative? Backwards: do the methods as you actually practised them imply a different position from the one you declared? Common mismatches include a constructivist position with a frequency-counting analysis, and a critical realist position with an analysis that never proposes generative mechanisms.
How do I evidence saturation?
State in advance what saturation means in your study, since no new codes, no new properties of existing categories and no change to the developing theory are three different thresholds. Then record where it was reached and report the evidence, for example the interview after which no new categories appeared and how many further interviews confirmed it. Saturation asserted without a rule and without evidence is one of the most frequently challenged claims in a qualitative viva.
What does good reflexivity look like?
Not a list of demographic characteristics followed by an expression of awareness. Analytic reflexivity names the specific ways your position plausibly shaped this study, says what you did about each, and reports what changed as a result. Reflexivity with no consequence is a performance.
How do I demonstrate trustworthiness in qualitative research?
By pointing at practices and the artefacts they leave, not by naming criteria. An audit trail is a dated record of analytic decisions built during analysis. Negative case analysis means actively searching for data that contradicts your account and reporting what it changed. Independent coding is evidence when the disagreements and their resolution are reported. If there is no artefact behind a criterion, do not claim it.
Should I pre-register my study?
It depends on the field, and the decision should rest on what it buys: it is the only credible way to separate confirmatory from exploratory analysis after the fact. If you do register, make it specific enough to constrain your analysis, and report every deviation with its reason. An unreported deviation found by an examiner damages credibility far more than the deviation itself.
The skill chain
Works well with.
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