Podwojski, Luke (2026) Science Won't Correct Itself: An Exploration of the Cumulative Knowledge Process. Bachelor's Thesis, Mathematics.
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Abstract
The pursuit of accuracy and quality in the process of knowledge production and accumulation is one of great importance, especially within the academic establishment. Despite the widely held belief of academia as a naturally-self correcting knowledge ecosystem, new evidence increasingly points towards the need for methods improving error eradication within academic publishing. One such probabilistic method is the Cumulative Knowledge Process, first proposed by Ben-Eliezer et al.. This thesis presents, supplements, and expands on the concept of the Cumulative Knowledge Process and selected results, based primarily on the work of Ben-Eliezer et al. and in part Brandenberger et al.. It is shown that there exist regimes under which error effects are eliminated or survive with positive probability for the simple and general model; in shallow checking procedures the error always survives with positive probability. Additionally, new results are shown concerning error effects in an adversarial variation of the model.
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Supervisor name: | Donderwinkel, S.A. and Szabo, R. |
| Degree programme: | Mathematics |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 08 Jul 2026 14:08 |
| Last Modified: | 08 Jul 2026 14:08 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/37405 |
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