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This research aims to redefine contributor screening by examining a drop-off rate through precision filtering.

April 23, 2026Open Access

114 to 9: What a Live Leaderboard Teaches You About Contributor Screening at Scale

Key Points

This research aims to redefine contributor screening by examining a drop-off rate through precision filtering.
Introduced a four-stage funnel of intent model for contributor screening.
Analyzed L1/L2/L3 task architecture within the screening process.
Examined the impact of transparency and data transition in contributor evaluation.
Identified a significant drop-off rate that emphasizes the need for precision filtering.
Showed that the funnel of intent serves as an effective model for evaluating contributions.
Highlighted early-career onboarding challenges linked to screening processes.

Abstract

Reframes a 92% drop-off rate as precision filtering. Introduces the funnel of intent as a four-stage conversion model for contributor screening. Analyses L1/L2/L3 task architecture, mock-to-live data transition, PR transparency as reputational accountability, and early-career implications for onboarding friction.

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