# Discipline Skeleton -- Content Analysis

**Library:** Public RAM. **Authored by:** Epistemic Output Layer (S4). **Consumed by:** S4 at Phase D overlay.

Use when the invoked Librarian discipline is `content-analysis`. Content analysis converts text/media into defensible, quantitative measurement through systematic coding. Attach the three-axis block per measured category.

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## Native Skeleton (preserve)

1. **Research Question and Corpus** -- what is being measured, in what corpus, across what time period.
2. **Unit of Analysis** -- sentence, paragraph, document, image, scene.
3. **Codebook** -- category definitions, exemplars, decision rules. Versioned.
4. **Coder Training and Intercoder Reliability** -- Krippendorff's alpha, Cohen's kappa, or equivalent. Per category.
5. **Coding Procedure** -- how double-coding was done, disagreements resolved.
6. **Frequency and Co-occurrence Tables** -- per category; cross-tabs where relevant.
7. **Quantitative Findings** -- prevalence, trend, comparison across corpus strata.
8. **Interpretation within Corpus** -- what the frequencies mean in context.

## Overlay Hooks

- Each **measured category finding** (e.g., "Frame X appears in 34% of articles; rising trend 2019-2024") is a claim slot.
- Typical claim type: descriptive. Transportability slot: `sampling_representativeness`. If the finding concerns a framing or interpretive construction, re-type as interpretive -- different slot.
- Intercoder reliability is an UPSTREAM evidence input; it is not the three-axis confidence. Do not fuse them.
- Surprise Register and Search Ledger render as top-level sections after Interpretation.
- Methodology trace: content-analysis tag, codebook version, reliability metric + value per category.

## Native elements that MUST survive overlay
- The Codebook (or its summary with version pointer).
- Reliability metrics per category.
- Frequency / co-occurrence tables.

Content analysis measures the corpus, not the world. Transportability rationale should name whether the corpus is representative of the decision-context's relevant media landscape.
