screening-then-scoring

name	screening-then-scoring
description	First eliminate non-qualifying candidates with non-compensatory rules, then score survivors with full MCDA methods.
execution	tactic
dependencies	{"sops":["alternative-scoring","conjunctive-filter","criterion-definition","dominance-check","normalization","scoring-synthesis","threshold-setting","weight-elicitation-sop"]}

Screening Then Scoring

First eliminate non-qualifying alternatives using non-compensatory rules, then perform fine-grained scoring and ranking of survivors. Suitable for scenarios with large candidate sets or hard constraints.

Stages

1. Threshold Setting — Set minimum thresholds for critical criteria
2. Conjunctive Filtering — Eliminate non-qualifying alternatives based on thresholds
3. Dominance Check — Identify dominated alternatives among survivors (optional further reduction)
4. Full Scoring — Execute scoring-matrix-construction workflow on survivors

Available SOPs

• threshold-setting — Set criteria thresholds
• conjunctive-filter — Conjunctive rule elimination
• dominance-check — Dominance relationship check
• criterion-definition — Fine-grained scoring criteria (Stage 4)
• weight-elicitation-sop — Weight computation (Stage 4)
• alternative-scoring — Alternative scoring (Stage 4)
• normalization — Normalization (Stage 4)
• scoring-synthesis — Comprehensive recommendation (Stage 4)

Execution Guidance

• Stages 1-3 are the screening phase, rapidly reducing the candidate set
• Screening criteria should focus on hard constraints (safety, compliance, budget caps, etc.)
• Survivor count should ideally be 3-8 before entering fine-grained scoring
• If too few survivors after screening (<3), consider relaxing thresholds
• If too many survivors (>10), add screening criteria or tighten thresholds
• Stage 4 reuses the complete scoring-matrix-construction tactic workflow

Minimum Yield

Elimination rationale + survivor ranking

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOP	When to use
alternative-scoring	Score each candidate alternative against all criteria to produce a score matrix.
conjunctive-filter	Apply conjunctive screening rules to eliminate candidates that fail any threshold.
criterion-definition	Extract evaluation criteria from research goals and candidate alternatives.
dominance-check	Identify dominated and non-dominated alternatives in a score matrix using Pareto dominance.
normalization	Normalize a score matrix using a specified method to make scores comparable across criteria.
scoring-synthesis	Synthesize score matrix, rankings, and sensitivity analysis into a final recommendation.
threshold-setting	Define minimum acceptable thresholds for each criterion based on context and constraints.
weight-elicitation-sop	Compute criteria weights using a specified elicitation method (AHP, Swing, BWM, MACBETH, or Simos).