Rigor Mortis

How Sloppy Science Creates Worthless Cures, Crushes Hope, and Wastes Billions

Richard Harris Central 610.72 H3158r 2017


About biomedical research, but the problems extend to many academic research fields.


My own brainfarts, after reading the book:

The core problem is too many academic scientists dividing up the available funding and jobs. Universities hire scientists as professors to train more scientists, who want jobs at those universities. If (WAG) three academic scientists produce ten new scientists every ten years over a 30 year career, and half of those new scientists seek grant-funded research jobs, then the number of scientists competing for those jobs doubles every 3.5 years. Funding for science is growing, globally, but not nearly that fast. Funding vacillates in countries like the United States, driven up and down by political and economic pressures.

This results in poorly trained new scientists, many lacking the statistical and logical training to identify and correct their own errors. It rewards careless boasters who make the biggest unsubstantiated claims, and paywall "prestige" journals like Science and Nature that are more concerned with glamor than replication and accuracy. Most articles are wrong, some dangerously. Many papers are cited carelessly by subsequent authors who have not even read (much less validated) those articles - I know, one of my papers has been cited more than 200 times.

Science publishing and science employment require radical restructuring. Ward Cunningham's "Federated Wiki" might be a good way to establish bidirectional links between "evolving" papers; no "published" paper stops improving. Erronious papers are identified, and are repaired or orphaned by originating and future authors. Rather than an exponential explosion of poorly supported work, the scientific community revises and develops its corpus of work (with the old revisions watermarked, timestamped, and carefully archived by multiple users of that work). Digital mass storage grows much faster than science does; we still need formatting experts, editors, and reviewers, but we don't need journals and we don't need paywalls anymore.

That might help with quality; there will be a broader range, from brilliant multiply-tested community creations to pseudoscience dreck. Dreck believers punish themselves; if that draws away marginal scientists and researchers, it helps deal with the scientific overpopulation problem.

Nonetheless, many good scientists can't find work as full-time scientists, like the professors they wish to emulate. Perhaps 10% can expect academic positions in their own field at the end of their training; in some over-producing fields like astronomy and physics, that might be closer to 3%. How do we relieve the pressure?

The downfall of science is overspecialization; newly trained scientists know how to do one narrow thing, and don't know how to talk about that to the citizens whose taxes pay for most research. ALL scientists should be crosstrained in at least one other field, such as business, engineering, medicine, manufacturing, education, law, politics, journalism, advertising, entertainment, and religion. Many will find fulfillment in their "second marriage", and can help inform those fields. This crosstraining can occur PRIOR to formal scientific training; a managed path for EARNING tuition before and during college can eliminate the crippling loans that many emerge from college with. If we take the debt-driven hurry out of science, we'll have time to do it right.

We also need more volunteer-driven public science. Ideally, everyone on the planet should contribute talent to the process; that will increase scientific productivity and public awareness. How to filter out the dreck? Darwinian selection by economic result. Most science affects (and is affected by) economic output; bad ideas turn into failed products. The trick is designing the scientific network (probably running on an evolved internet substrate) to back-propagate economic value in return for forward-propagating scientific value. Discovering a robust and stable "science economy" won't be easy, but it can evolve from small successes.

Wikipedia came from wiki, which came from html and Apple's hypercard. Wikipedia will never be perfect, but it evolves. When it gets too big, it will split into competing but federated wikis, and users will interact through adaptive interfaces. Computers evolved from mainframes with terminals, to personal computers, to mainframes (server farms) with terminals ("dodopaddle" smartphones) again. Search is currently "mainframed", but with the right tools, personal computers can host the search themselves, accessing millions of tiered sources of raw data. This could evolve into the new "science economy", when researchers connect their labs and their own raw data into this widely distributed network.

Professional scientists are isolated their customers, funders, and from effective self-regulation. This does not elevate them into an elite, but plunges them into a poverty-stricken ghetto, and robs the rest of us of the bounty that collaboration will bring.


RigorMortis (last edited 2018-01-09 04:48:22 by KeithLofstrom)