# Collective review

`kaal:entity:collective-review`

**Status.** derived

This node is assembled mechanically from the 3 claims that carry the concept tag `collective-review`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

3 claims across 3 works, 2021 to 2024.

**2021**

- [3995709-013](https://wulfkaal.github.io/claims/3995709-013) [mechanism/argued] *(failure mode)* -- In hierarchical legacy review processes the first reviewer's output gets the highest priority and follow on reviewers add only minor upgrades, so the collective of reviewers is not incentivized to find flaws and optimize the code as a collective work product.
  > often gets the highest priority and is often merely followed with minor upgrades by follow-on reviewers. The collective of reviewers is also not incentivized to find flaws in the code to optimize code as a work product of the collective.
  Wulf A. Kaal, How DAOs Optimize Open-Source Code Reviews and Create Open-Source Standards (2021). SSRN: https://ssrn.com/abstract=3995709

**2024**

- [4734750-008](https://wulfkaal.github.io/claims/4734750-008) [failure/argued] *(failure mode)* -- In hierarchical review, the first reviewer's output receives the highest priority and later reviewers add only minor upgrades, so the review becomes the initial reviewer's work product rather than the collective's.
  > The collective of reviewers is also not incentivized to find flaws in the code to optimize code as a work product of the collective. Rather, it is often seen as the work product of the initial reviewer with minor input from follow-up reviewers.
  Wulf A. Kaal, Code Review DAO (2024). SSRN: https://ssrn.com/abstract=4734750
- [4755632-019](https://wulfkaal.github.io/claims/4755632-019) [failure/argued] *(failure mode)* -- The collective of reviewers in legacy code review is not incentivized to find flaws in the code, because the review is treated as the work product of the initial reviewer with minor input from follow-up reviewers rather than as a product of the collective.
  > The collective of reviewers is also not incentivized to find flaws in the code to optimize code as a work product of the collective.
  Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024). SSRN: https://ssrn.com/abstract=4755632

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/collective-review.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.