/surveying-prior-work

name: surveying-prior-work
description: Use after framing a question and before designing an analysis, or when choosing a method, judging whether a result is novel, or needing a prior effect size for a power calculation

Surveying Prior Work

Overview

Before designing an analysis, ground the question and your chosen methods in what is already known. Most questions have established methods, known confounds, and prior effect sizes. Reinventing a method badly — or rediscovering a known artifact and reporting it as a finding — wastes effort and erodes credibility.

**Core principle:** Find out what is already known before you generate new claims.

This is the science analog of reading the existing codebase before writing new code. It is a flexible skill — adapt depth to the stakes of the investigation.

When to Use

• After `framing-research-questions`, before `designing-the-analysis`
• When selecting a statistical method or model and unsure what is standard
• When a result looks novel — check whether it is a known effect or artifact first
• When you need a plausible prior effect size to power the study
• When you suspect confounds but don't know which are established in the field

What to Ground

Survey four things:

1. **Established methods** — what is the standard, accepted way to analyze this kind of question? What are its assumptions and failure modes? 2. **Known confounds and artifacts** — what variables are known to drive this outcome? What measurement artifacts are common in this data type? 3. **Prior effect sizes** — what magnitude have others found? This feeds the power/sample-size calculation in the analysis design. 4. **Relationship to prior work** — is this a replication, an extension, a new population, or genuinely novel? Be honest about which.

The Process

1. **List what needs grounding** — turn the "open questions for prior-work survey" from the question document into concrete search targets. 2. **Search** — use web search and any available literature tools for published methods and effect sizes; search the repo and your human partner's prior analyses for in-house precedent and conventions. 3. **For broad surveys, dispatch parallel subagents** — one per independent sub-topic (a method, a confound, a prior estimate). REQUIRED: use `science-superpowers:dispatching-parallel-investigations` for the workflow. This keeps your own context clean. 4. **Synthesize** — write a short prior-work note (or a section appended to the question document):

• Established method(s) you will adopt and why
• Confounds you must measure or control for
• Prior effect size(s) and the source, for powering the design
• Honest statement of how this investigation relates to prior work

5. **Cite sources** — record where each fact came from so the design and final report can reference it. When you present findings from web search, follow your platform's citation standards.

Red Flags

• Reaching for a method you invented when a standard one exists → find and use the standard one (or justify the deviation explicitly)
• Designing the analysis with no idea what effect size to expect → you skipped the power input; survey first
• About to report something as novel without having checked → search first; novelty is a claim that needs evidence
• Ignoring a confound because checking is inconvenient → known confounds are not optional

Handoff

After grounding, invoke `science-superpowers:designing-the-analysis`. Bring forward the adopted methods, the confound list, and the prior effect size for powering the design.