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category-development

Use when developing and densifying categories with properties, dimensions, conditions, and consequences.

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ccashwell/qualitative-research-pro
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11 avril 2026 à 02:10
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category-development
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Use when developing and densifying categories with properties, dimensions, conditions, and consequences.
# Category Development and Densification A **category** is a higher-order concept that groups related incidents under an abstract label. Dense categories specify **properties** (characteristics) and **dimensions** (ranges along which properties vary), plus **conditions** under which patterns hold and **consequences** that follow. ## From code to category Move up a level when multiple codes repeatedly co-occur or share a latent pattern. Rename categories using **participant-relevant** language when possible (in vivo lift), then refine to conceptual clarity. ## Properties and dimensions - **Property:** what kind of thing this category is (e.g., “visibility” as a property of stigma management). - **Dimension:** the range (high/low, public/private, formal/informal). Example: if “time pressure” is a category, properties might include *source* (institutional vs interpersonal) and *duration* (acute vs chronic); dimensions map variation across cases. ## Conditions and consequences Ask: - **When** does this category appear? **Under what conditions** does it intensify or disappear? - **What follows** from it—emotionally, interactionally, structurally? Use **conditional matrices** (see `visual-modeling`) when relationships multiply. ## Densification through comparison Compare incidents within the same category to discover **new properties**. Compare across categories to locate **boundaries** (what this category is not). ## Thin vs thick categories A **thin** category is a label without variation spelled out. A **thick** category has: - Clear definition. - Exemplar incidents. - Property/dimension map. - Known conditions/consequences. - documented negative cases. ## Relationship to saturation Saturation is **about categories**: you stop sampling for a category when fresh data no longer reveals new properties/dimensions relevant to your emerging theory. Some peripheral categories may remain thin if they are not theoretically central—justify that choice. ## Category profile template (use in memos) - **Name:** - **Definition:** - **Exemplars (IDs):** - **Properties & dimensions:** - **Conditions:** - **Consequences:** - **Related categories (hypothesized links):** - **Negative cases:** ## Worked example (abbreviated) Category: **“Patching workarounds.”** - Property: *visibility* (hidden vs visible to management). - Dimension: *risk* (low vs high sanction). - Condition: arises when formal protocols conflict with patient safety pressures. - Consequence: temporary relief but accumulates moral distress. ## Checklist - [ ] Category defined at one conceptual level (not a grab-bag). - [ ] Properties/dimensions extracted via comparison. - [ ] Conditions/consequences hypothesized and tested with new data. - [ ] Negative cases actively sought. - [ ] Links to core category articulated as the theory matures. ## References (starting points) - Glaser, B. G. *Theoretical Sensitivity* — theoretical coding families and category logic. - Strauss, A., & Corbin, J. *Basics of Qualitative Research* — conditional/consequential thinking (read critically alongside Glaserian distinctions). - Konecki, K. *Visualizing Grounded Theory* — diagrams for category relations.
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