Simfish/InquilineKea's Thoughts


model of scientific research
January 2, 2010, 10:47 pm
Filed under: Uncategorized

normal science: adding entries to the database of scientific knowledge (entries are categorized and analyzed according to current rules)

revolutionary science: change the rules. or design a totally different new system of rules that makes the entries in the database more consistent with each other.

there are several levels of normal science. a researcher/principal investigator can allocate most of the “normal science” work to graduate students/others as he can usually expect them to follow the procedures of normal science. occasionally the researcher chooses to look at the data more closely/examine the data, as specific instances can provide “schema/prototypes” to help clarify theory (and make the theory more salient and comprehensible)

Also, the “4 paradigms” – theory, experiment, simulations, data mining/pattern recognition. technically the latter two can be considered subsets of experiments. But at the same time, they also share some characteristics with theory. there’s a new computer program that can derive physical laws from mass datasets. how does one categorize that? it’s clearly the fourth paradigm, but at the same time, it creates theory (and theory is inspired by the desire to find a model/equation to make the data consistent). simulations can be analyzed too (simulations are pretty much experiments – the only difference is that simulations do not have to conform to the real world). in fact, a lot of the “normal science work” consists of the analysis of simulation output, as many simulations are ad hoc and haven’t been independently investigated by numerous people.

Also, we now know that crowdsourcing can also inspire research (usually through categorization/data mining/etc). Some sorts of crowdsourcing were implicitly used in empirical research (e.g. many fossils are not discovered by people who are actively looking for them – they just accidentally dig them up). now crowdsourcing is more active (galaxy identification, etc).

Technically, there are other important steps to further research too. developing the infrastructure of research (through engineers and programmers). a lot of the infrastructure is general and must be converted to scientific uses.

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Methods of scientific research:

– using alternative paradigm to investigate data. sometimes alternative paradigm describes data better; sometimes data is described equally well by multiple paradigms/interpretations

– development of infrastructure (and integration thereof). matlab, python modules, toolkits, etc.

– run simulations, see if simulation outputs confirm paradigm

– lit reviews (they get the most citations!)

– structure of object, structure of object’s interactions

Personality Psychology:

– Comparing self-assessments with external assessments, assess both wrt accuracy

Psychopharmacology:

– Compare one drug’s effects in adolescence to its effects in adulthood

– bioavailability/pharmokinetics/toxicology/etc. anything on its spec sheet

– effects of metabolites

– effects on other disorders

– possible chronic effects

CS:

– two systems are developed independently from each other. often research (the lowly kind assigned to undergrads) is to link up the systems with each other (by making them able to communicate with each other [directly or through output files/reading output files], or by individually converting the code in one system to the code in another system. )
– rewriting code so that it can be run by parallel/distributed processes

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