think-affinity-mappinglisted

<!-- thinking-framework-skills | https://github.com/product-on-purpose/thinking-framework-skills | Apache-2.0 --> # Affinity Mapping Affinity mapping takes a pile of many individual items - raw notes, observations, quotes, data points - and groups them *bottom-up by felt similarity* until a small set of emergent themes appears, then names each theme so the names become the structure. The load-bearing move is **deferred, bottom-up categorization**: you do not sort items into predefined buckets, you let the categories surface from the items themselves. This externalizes comparison so patterns hidden in a linear list become visible, resists the frame you walked in with, and compresses many items into a few themes while keeping every item traceable to its theme. The output is a **clustered theme map**, not a discussion. ## When to Use - When dozens to hundreds of existing items - user-research notes, interview quotes, support tickets, survey free-text, retro stickies, workshop output - need to become a few themes. - When the right structure is not known in advance and should emerge from the data rather than be imposed. - When the items already exist and the job is synthesis, not generation. - When traceability matters: you want each theme to point back to the specific items that support it. ## When NOT to Use - **When there are only a handful of items.** With a dozen or fewer you can reason about them directly; the clustering ceremony adds overhead without insight. - **When