Tag: Scientific Process

…but is it science?

Granted, this kid seems creative & entrepreneurial – the next generation of Maker; but why is building a marshmallow cannon science? I can think of a number of ways building and testing a marshmallow cannon could illustrate the scientific method. Successfully constructing a marshmallow cannon, however, is an engineering challenge – very suitable for a Maker Faire, but why is this a top Science Fair project?

In fairness to the marshmallow cannon, descriptions of the award-winning projects all sound like engineering or invention projects rather than exercises in the scientific method. I like gadgets and inventions, but is it small wonder that we are a scientifically illiterate society when even our Science Fairs don’t know what science is?

The NCI wants to fund the non-obvious

The National Cancer Institute wants researchers to start asking non-obvious questions.

I suppose that’s good, because the NIH’s very conservative funding process is one reason why so many researchers focus on the obvious questions. On the other hand, it’s not so clear that answering non-obvious questions lead to more insight than answering obvious questions. The question can be obvious or non-obvious and still generate that key to scientific progress, the unexpected answer.

Italo Calvino on how to build models of the world

Brilliant and hilarious, from Mr. Palomar, over at Gene Logic.

Confusing data with theory

Maybe because experiments can be so much work, molecular biologists are just happy to have the data:

Krakauer, et al. “The challenges and scope of theoretical biology”, Journal of Theoretical Biology Volume 276, Issue 1, 7 May 2011, Pages 269–276:

The current absence of a strong theoretical foundation in biology means that there is weak guidance regarding what quantities or variables need to be understood to best inform a general understanding (an explanatory basis) for biological features of interest. An unfortunate result of the absence of theory is that some researchers confuse just having data with ‘understanding’. For example there is a base for collecting and analyzing the most microscopic data: experimental procedures and measurements in a high-throughput transcriptomics study are built around the assumption that transcripts are the primary data to be explained, and in neuroscience, recording from numerous individual neurons. This bias reflects a rather naive belief that the most fundamental data provide a form of explanation for a system, as if enumerating the fundamental particles were equivalent to the standard model in physics.

And here is this kind of thinking in action:

Nurse and Hayles. The cell in an era of systems biology. Cell (2011) vol. 144 (6) pp. 850-854: Continue reading “Confusing data with theory”

Why to avoid a science career…

Yep:

“Academia’s Crooked Money Trail”, by Beryl Lieff Benderly, over at Science Careers

The troubles plaguing academic science — including fierce competition for funding, dismal career opportunities for young scientists, overdependence on soft money, excessive time spent applying for grants, and many more — do not arise, Stephan suggests, from a shortage of funds. In 2009, she notes, the United States spent nearly $55 billion on university- and medical school–based research and development, far more than any other nation.

The problems arise, Stephan argues, from how that money is allocated: who gets to spend it, where, and on what. Unlike a number of other countries, the United States structures university-based research around short-term competitive grants to faculty members. The incentives built into this system lead universities to behave “as though they are high-end shopping centers,” she writes. “They turn around and lease the facilities to faculty in [exchange for] indirect costs on grants and buyout of salary…” Continue reading “Why to avoid a science career…”