nw-rr-critique-dimensions

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Critique dimensions and scoring for research document reviews

AI & Automation 526 stars 55 forks Updated 1 weeks ago MIT

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Skill Content

# Critique Dimensions for Research Review Load when reviewing research documents. Apply each dimension systematically. ## Dimension 1: Source Selection Bias Check: contradictory viewpoints included? | Multiple organizations/authors/perspectives? | Geographic/temporal diversity? | Sources truly independent (not circular)? Flags: 60%+ from single org/author -> critical | All supporting same conclusion without counterpoint -> critical | Single geographic region -> medium | Clustered publication dates -> medium ## Dimension 2: Evidence Quality Check: every major claim cited | sources reputable (peer-reviewed, official, established) | primary over secondary | technical sources recent (5 years) | confidence matches evidence Flags: uncited claim -> high | blog/forum for factual claim -> high | all secondary sources -> medium | sources >5 years for tech -> medium | high confidence with 1-2 sources -> high ## Dimension 3: Replicability Check: search strategy documented | source selection criteria explicit | methodology transparent | confidence levels with rationale Flags: no methodology section -> high | vague methodology ("searched the web") -> medium | no confidence ratings -> medium ## Dimension 4: Priority Validation For research driving architectural/strategic decisions. Q1: Is this the largest bottleneck? (timing/measurement data?) | Q2: Simpler alternatives considered and rejected with evidence? | Q3: Constraint prioritization correct? (>50% solution for <30% probl...

Details

Author
nWave-ai
Repository
nWave-ai/nWave
Created
3 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

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