Science

History, sociology and philosophy thereof

2017-07-08 — 2025-05-23

academe
agents
collective knowledge
economics
faster pussycat
game theory
how do science
incentive mechanisms
institutions
mind
networks
provenance
sociology
wonk
Figure 1

I spend a lot of time thinking about science: what it is, how it works, and how it fails. It’s the best tool we have for understanding reality, but the human systems we’ve built around it are a glorious, frustrating, and endlessly fascinating mess. This collection of notebooks is my attempt to map that mess. It covers everything from the byzantine economics of academic publishing to the quiet cognitive habits that lead to discovery. What follows is not a unified theory, but a series of interconnected dispatches from the front lines.

A Reader’s Guide

This is a sprawling collection. Here are some suggested entry points:

0.1 The Engine of Science

Creating Scientific Knowledge: How does research get started? This post examines the inputs and incentives of science—the economics of grants, the sociology of ideas, and the culture that decides which questions are worth asking.

Research Discovery & Synthesis: Before you can contribute, you have to find out what’s already known. This post surveys the tools and theories for navigating the deluge of existing research, from search engines to AI assistants.

Disseminating Science: How is new knowledge shared? Here we look at the mechanisms of publishing, the culture of conferences, the role of preprint servers, and the controversial world of shadow libraries.

Validating & Reproducing Science: How do we know if it’s true? This section focuses on the messy business of quality control: peer review, the replication crisis, and the gatekeeping systems designed to ensure science is trustworthy.

0.2 For the Working Scientist

A Scientist’s Survival Guide: This is a guide to the messy, practical business of being a researcher. It covers everything from navigating the funding labyrinth and the art of networking to the quieter, internal habits of mind that foster discovery.

0.3 Designing Research Systems

Building Scientific Institutions: How do we design research machines? This post examines the organizational patterns that foster innovation, from Bell Labs to modern FROs, and the management principles that either accelerate or suffocate scientific progress.

0.4 Science and Society

Science Communication: How do we make science understandable and compelling to broader audiences? This covers the tools, techniques, and challenges of translating complex research into accessible stories.

Science for Policy: How should scientific evidence inform government decisions? This explores the interface between research and policymaking, including the challenges of uncertainty, expertise, and democratic governance.

Science in Australia: A case study in how national science systems work in practice, examining Australia’s unique approach to research funding, institutional design, and the particular challenges of doing science in a middle power.

0.5 Other Explorations

History of Medicine: Understanding how we got here by examining the evolution of medical knowledge and practice.

ML Benchmarks: The science of algorithms presents unique challenges for validation and progress measurement.

Citizen Science: How non-professional scientists contribute to research, and what this tells us about the democratization of knowledge creation.

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