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theoretical-sensitivity

Use when developing the researcher's ability to see conceptual possibilities in data, to recognize what is important, and to give meaning to data.

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
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theoretical-sensitivity
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Use when developing the researcher's ability to see conceptual possibilities in data, to recognize what is important, and to give meaning to data.
# Theoretical Sensitivity **Theoretical sensitivity** is the researcher’s ability to **see meaning in data**, to discern **what matters conceptually**, and to imagine **plausible relationships** among categories—without **forcing** preconceived ideas onto participants’ experiences. Glaser treats sensitivity as a **craft**: developed through analytic practice, disciplined comparison, and curated reading—not through importing a ready-made framework for the substantive area too early. Use this skill when you feel “stuck” in description, when codes multiply without insight, or when you need to **calibrate openness** versus **conceptual discipline**. --- ## Glaser’s concept (1978): what sensitivity is not **Sensitivity is not**: - Cleverness at inventing jargon. - A license to impose pet theories. - The same as “being smart about the topic” before data collection. **Sensitivity is**: - Recognizing **indicator-rich** incidents. - Hearing **process** and **variation** rather than only content. - Knowing **when** to code, **when** to memo, and **when** to sample next. --- ## Sources of theoretical sensitivity (classic GT) ### 1) Personal experience (used carefully) Your biography can sensitize you to emotional tones, organizational rhythms, or interactional subtleties. **Risk**: autobiographical projection. **Mitigation**: treat personal resonance as a **cue to memo**, then **compare** across cases; seek **negative cases**. ### 2) Professional experience Prior practice in a domain (e.g., nursing, engineering, teaching) can help you notice **routine expertise** and **tacit norms**. **Risk**: expert blinders (“that’s just how it is”). **Mitigation**: convert expertise into **questions**, not answers; privilege **participants’** problem-solving. ### 3) Analytic experience within the study As codes mature, you become sensitized to **patterns**, **absences**, and **deviance**. This is the **strongest** engine of sensitivity in GT. **Practice**: regular **memo sorting** and **hypothesis revision**. ### 4) Literature **outside** the substantive area Glaser encourages reading broadly in sociology, psychology, anthropology, philosophy of science, etc., to build a **repertoire of concepts** and **metaphors** that can **suggest** comparisons. **Key move**: use external literature to **stimulate imagination**, not to **name** the phenomenon prematurely. ### 5) Literature in the substantive area (timed) Substantive-area literature becomes more appropriate **later**, often as **additional data** for comparison **after** emergence stabilizes—never as a substitute for participants’ lived problem-solving. --- ## How to cultivate sensitivity (concrete practices) ### A) Comparison drills Each session, run **three comparisons**: 1. two incidents within the same code 2. one incident against an emerging **hypothesis** 3. one incident against a **negative case** candidate ### B) “What is this a study of?” prompts Ask repeatedly at different grains: - Of this **line**? - Of this **incident**? - Of this **interview**? - Of the **project** today? ### C) Gerund reframing Rewrite nouns into **process language** to reveal action/interaction. ### D) Memo-first discipline When a strong interpretation appears, **memo** before expanding coding—capture **scope**, **conditions**, and **counterexamples** you already know. ### E) Codebook hygiene Rewrite definitions when they become **too vague** (“stress”) or **too literal** (topic labels). Good definitions sharpen sensitivity for the **next** pass. --- ## Threats to sensitivity (and fixes) ### Preconception **Symptom**: every incident “supports” your favorite theory. **Fix**: actively seek **disconfirming** incidents; split codes when variance appears; invite **outsider** debriefing. ### Forcing (template thinking) **Symptom**: codes map 1:1 onto a model you imported. **Fix**: remove the template from sight during early passes; rename codes using **data-grounded** language. ### Sentimentality / moralizing **Symptom**: analytic language becomes judgmental (“bad management”). **Fix**: translate judgments into **processual** categories (*managing accountability*, *externalizing blame*)—still critical, but **conceptual**. ### Premature closure **Symptom**: “we already know the story.” **Fix**: theoretical sampling aimed at **boundaries**; revisit **early** transcripts with new eyes. ### Tool obsession **Symptom**: perfect software tags, thin thinking. **Fix**: short, messy **memos** beat pristine code taxonomies. --- ## Exercises for building sensitivity ### Exercise 1 — One paragraph, ten codes Take one dense paragraph. Generate **10 distinct substantive codes** (some will be wrong). Then **merge** aggressively after comparison. Goal: **fluency** and **differentiation**. ### Exercise 2 — In vivo extraction Highlight participant phrases that could be **in vivo** codes. For each, write a **one-sentence** translation into more general concepts. ### Exercise 3 — Hypothesis ping-pong Write **three** competing hypotheses for the same incident. Use next data to **eliminate** or **revise**. ### Exercise 4 — Literature spark (outside area) Read a short unrelated theory piece. Write **two memos**: (a) “What concepts might illuminate my data?” (b) “How could this **mislead** me if forced?” ### Exercise 5 — Negative case journal Maintain a running list: **anomalies**, **silences**, **refusals**, **surprises**. Revisit weekly. --- ## Outputs that demonstrate growing sensitivity - Memos that specify **conditions** and **consequences**, not only themes. - Codes with **properties/dimensions** discovered through comparison. - Sampling memos that target **gaps** rather than convenience. - A core category that **survives** deviant-case scrutiny. --- ## Key references - Glaser, B. G. (1978). *Theoretical sensitivity: Advances in the methodology of grounded theory*. Sociology Press. - Glaser, B. G. (1992). *Basics of grounded theory analysis*. Sociology Press. - Glaser, B. G. (1998). *Doing grounded theory*. Sociology Press. --- ## Companion skills - `memo-writing`, `constant-comparison`, `open-coding` - `theoretical-sampling`, `selective-coding` - `glaserian-grounded-theory`
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