Open the complete text-first lecture packageSix-minute Pareto and ablation example. The current equivalent is notes, slide script, worked case, and no-video transcript; no recording is claimed.
Readiness check
List two objectives, one budget, and three non-negotiable constraints.
Bring
Preregistered objective and choice-rule card.
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Explanation
Concepts, assumptions, and boundary
One intervention serves multiple intents
Content changes can help one query class while harming another. Optimization therefore needs a declared portfolio, objective vector, query weights, content or cost budget, and hard factual, legal, safety, and accessibility constraints. A weighted sum is a policy choice, not a natural truth. Pareto analysis makes trade-offs visible by showing solutions that cannot improve one objective without worsening another.
Ablation tests the mechanism claim
An ablation removes or varies one component while preserving the rest of the design. The analysis should report per-stratum effects, dominated solutions, constraint violations, and uncertainty. Selecting weights after viewing results turns the objective into another researcher degree of freedom. The choice rule, tie handling, and failure threshold are therefore frozen in advance, and a null or conflicting result remains a valid outcome.
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Primary visual
Inspect the mechanism or evidence structure
Synthetic illustrationConstrained Pareto choice—schematic only
Figure design. A not-to-scale two-objective diagram distinguishes an illustrative nondominated frontier, dominated candidates, and a constraint-excluded candidate. It contains no observed values, sample size, or uncertainty estimate. Schematic candidate positions are not observations or estimates. Weights express policy; facts and safety remain non-negotiable.Long description
Seven deliberately schematic candidate positions occupy axes labeled Objective A and Objective B. Five illustrative points form a frontier, one is dominated, and one crossed point is excluded before choice by a hard constraint. Positions do not represent a dataset or estimate.
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Interactive check
One action, one feedback state
Action
Move objective weights and inspect which solutions become dominated or violate constraints.
Feedback
The state reports the implied policy choice and never permits factual integrity or safety to become a soft weight.
Accessible alternative
A table enumerates all weight settings and selected solutions.