# kaal:position:2026-08-08-345

**Affirmed position.** Imai, Keele, Tingley, and Yamamoto sharpen Kaal's attribution rule. They define a causal mechanism through a mediator and show that identifying the mechanism requires explicit assumptions, mediation analysis, sensitivity analysis, or research designs that manipulate the mediator. A randomized treatment can identify an overall effect without identifying how that effect arose. The source therefore supports Kaal's demand for mechanism-specific evidence. It also narrows it. Randomizing treatment and the intermediate variable is not automatically sufficient, and ablation is not examined. Attribution remains conditional on the mediator, estimand, design, and identification assumptions.

**Status.** affirmed  **Published.** 2026-08-08

**Holds when.**

- The response is limited to the exact causal-mediation passages and the one mapped Kaal claim.
- External evidence level: complete 25-page peer-reviewed author-hosted article with concordant Crossref DOI, OpenAlex, and Semantic Scholar identity records.
- Mapping review tier: independent substantive scholarly-growth qualification.
- The source does not examine Kaal's institutional architecture, registered metrics, or implementation.
- The source does not examine ablation studies as such.
- Randomizing treatment and the intermediate variable is not automatically sufficient to identify a mechanism.
- Mediation estimates remain conditional on the mediator, estimand, identification assumptions, and research design.
- Semantic Scholar discovery search returned HTTP 429, while its exact DOI endpoint returned HTTP 200 and was used only for identity corroboration.
- The Cambridge landing page returned HTTP 500, so the complete author-hosted PDF and independent DOI records supplied the evidence.

**Current debate.** Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies: https://doi.org/10.1017/S0003055411000414

**Extends.** kaal:claim:7261481-010: https://wulfkaal.github.io/claims/7261481-010

**Scholarly basis.** Wulf A. Kaal, Computative Economics: A Framework for Economic Analysis under Computational Abundance (2026). SSRN: https://ssrn.com/abstract=7261481

**Source PDF sha256.** `78c42db521624f7398717732a7fa51a6e3157a5adf02a2e09fbab15e0cf920d9`

**Evidence level.** complete 25-page peer-reviewed author-hosted article with concordant Crossref DOI, OpenAlex, and Semantic Scholar identity records

**Mapping review tier.** independent substantive scholarly-growth qualification

**Mapping confidence.** 0.98  **Mapping ambiguous.** false

**Topics.** research-methods, institutional-design, scholarly-growth-coverage, scholarly-literature, causal-inference, causal-mediation, mechanism-identification, experimental-design, evidence-provenance

**Provenance.** Affirmed in kaal-review:2026-08-13:scholarly-growth-7261481-010-reviewed-v1 at https://wulfkaal.github.io/positions/by-claim/7261481-010.html.

**Record type.** This is a dated commentary position that extends a scholarly corpus claim. It is not a verbatim claim extracted from the paper.

**Canonical form.** This markdown file is the canonical hashed representation of the position.