Saturday, January 31, 2009

Reality's Yard Stick

The closest I've come to the language of "measurement" before reading Williams, Lauer & Asher, Morgan, and Goubil-Gambrell was when I was rooming with a graduate student in cognitive psychology, who, after entering the dissertation phase of his work, would travel to Chicago schools and conduct what I now can label correlational studies of ADHD.  I liked listening to him.  The literature he was immersed in sounded like a foreign language.  And although he had no great love for it, he was passionate about what it could describe.

I enjoy learning new languages.  The grammar of measurement, however, is based on calculation, a muscle that I haven't trained in a long time and probably wasn't all that big to begin with.  So I apologize in advance if some of the questions listed below are ignorant of the obvious.  First, some definitions.

Qualitative  & Quantitative

Morgan is most helpful distinguishing qualitative research and its subgenres of ethnography, case study, and description as best serving research designs "concerned with process and description" (27).  Goubil-Gambrell adds that the method is particularly valuable in "identifying key variables" (584) and can be distinguished also by its lack of  "treatment" (which, in its "administration" reminded me of the menu of treatments spas let you choose from) (588).  

Since Goubil-Gambrell as well as the prompt for this blog constructed "qualitative" in opposition to "quantitative," I'm going to assume that Morgan's categories of "correlational studies" and "experimental studies" both make up the quantitative category, the former being more concerned with relationships, the latter with "outcomes or effects" (26).  Williams prefers the terms "descriptive method" and "experimental method" but they seem, especially in reference to treatments and variables, to overlay "qualitative" and "quantitative" (9).

Validity & Reliability

These were the most difficult terms to parse.  Lauer and Asher offer this: reliability "is the ability of independent observers or measurements to agree" (134); validity is the ability of a "measurement measure whatever it is intended to assess (in these introductory survey of terms, terms tend to repeat) (140).  Goubil-Gambrel isn't particularly helpful with the brief definition of validity being "whether the experiment actually measures what it says it will measure" and reliability "refers to whether the experiment precisely measures a single dimension of human ability" (587).  It being the most obscure, I wish I had read that definition first rather than last.  

Still, after going through Lauer and Asher's handling of the two terms, I'm somewhat confident concluding reliability often calibrates inward—among its own elements, both those of the study (measurement instrument) and those of the studiers (interraters), to determine if they are equivalent and consistent—before turning outward to judge if the results can be repeated under the same conditions.  Validity, on the other hand, focuses more on calibration of the result itself, how it relates with past and future studies, how well "the researcher measures what he claims to measure" (Williams 22).

Probability & Significance

Probability is the frequencies of (population, sample or sampling) distributions, "generalized to cases where there are different total numbers of units involved," such as, to take an example from Williams, the probability of coming up "heads" after 64 coin tosses, a number based on the frequency of generating that result.

Next step: probability becomes vital when it comes to the null hypothesis, that which must be rejected in order for grounds of a research hypothesis.  The probability level, then, is a "criterion for rejecting a null hypothesis" (61).  If the studies measure comes in under or equal to the established probability level, the null hypothesis can be thrown away.   (I'm assuming that the null is something everyone wants to avoid or get beyond, the research hypothesis being a kind of imprimatur.  This could be very wrong.)

The level of this probability, this zone of "accept or reject," becomes the "significance level": "if a calculated value of probability is such that it falls within the rejection region, the researcher will often call whatever difference or relationship he is studying statistically significant" (Williams 61).

I had a minor epiphany when reading this section of the text: the "significant" language of CNN polls and medical findings suddenly became clear.


Some confusion lingers.  Some of this is just musing.

Lauer and Asher say "reliability is to a large degree a social construction" (134).  Then they say that "validity depends in important ways on social consensus" (141).  So are both social constructs?

Morgan asserts that "experimental designs are different [from correlative and descriptive designs] in another way: comparison" (37).  So how do you do correlation without comparison?  

Goubil-Gambrell tells us that "the reason for all the statistical apparatus in quantitative research is to explain that relationships between variables are due not to chance but to cause-and-effect relationships" (586).  How does this square with Williams admitting "our knowledge of the laws of chance" informs us about the "degree of variation" among samples" (43).  This "knowledge" of sampling underpins probability which governs the whole "null" or "research" decision—a huge point of accuracy and distinction.  My question then: how much do you need to know about chance for it to become knowledge?  And isn't that then a little, what's the word....chancy?  To call chance predictable or consistent leaves me scratching my head, even though I know they list the "odds" on the back of a scratch ticket.

Aside 1: I love it when Morgan calls theory a "bin" (28).  I take my bins to the recycling center every week, otherwise they start to stink.  How big is your bin?

Aside 2 (and this isn't sarcastic):  I find it fascinating how quantitative research generates particular language (see Williams 58, 67)

Lastly, Williams (23) and Lauer and Asher (145) claim that you can get to reliability through validity, but not vice versa.  Again, I'm probably confusing something basic, but it seems to me that a valid result can be generated in an experiment, but it might not be based on reliable measurement tools.

I hope there has been some "truth value" to all of this.

Thursday, January 22, 2009

This One Goes Here, That One Goes There!

A circular arrangement:

Garret is: classification.
Miller is: classification.
Plato is: classification.
Hackos and Redish is: classification.
Kinneavy is: classification
This blog is: classification.

This, then that, then this, then that, then he goes here, then she goes there, etc.

Kinneavy: "Classification, on the other hand, is not concerned with the unique thing, but with things as members of groups" (7).

And later: "In each case I consider the attributes which the object possesses in common with other members of a given group" (8).

Or, in the words of Bravo: "Are you in or are you out?"  I was usually out.  No one picked me in gym class.  I was only good at soccer.  Dodge ball left me covered in large red welts.

Garret: "The skeleton is designed to optimize the arrangement of these elements for maximum effect and efficiency" (22).  Classification in action.  Arrangement mobilized.  Cut In and Cut Out to maximize profit margins.  "Now we can map that whole confusing array of terms"—because things must find their place, meanings must be locked down, the gates must be closed—"By breaking each plane down into its component elements [divide, divide, divide], we'll be able to take a closer look at how all the pieces fit together [unify, unify, unify] (31).  

That's how things make sense.  That's how people are paid and accounted for: "It's not necessary to have a member of your team who is a specialist in each of these areas; instead, you only have to ensure that someone is responsible for thinking about each of these issues" (35).  It's the language of efficiency. 

In Miller there is practical and there is non-practical.  There is in-the-classroom and there is in-the-workforce. There is descriptive and there is prescriptive.  There is good and there is non-good.  "My discussion so far has relied on a set of related oppositions that pervade the discourse of higher eduction" (21).  Miller tells us we're full of oppositions.  He lists them. 

inquiry versus action
gentleman-scholar versus technician-dupe
contemplation versus application
general versus general
etc. versus etc.

Oppositions, binaries, contrasts—they are the tools of classification.  And they "pervade our discourse." We are a departing constantly over our divisions.

This all, of course, goes back to Plato.  The master divider.  The great kicker-outer.  He demands that speech must be defined.  Rhetoric split from dialectic.  Knack from knowledge.  Soon after discussing Tisias, the professional sophist, Socrates concludes "unless a man take account of the characters of his hearers and is able to divide things by clases and to comprehend particulars under a general idea, he will never attain the highest human perfection in the art of speech."  If you are not dividing, if you are not classifying, if you are not working dialectically, you are wiping up the garbage.  You're a mess.  You're a mass of indistinct red welts.

Hakos and Redish turn the scalpel to movement.  Work will be split from Jobs.  Tasks from Goals.  Processes from Sequences.  Environment from Culture.  Noise from Hazards.  "We can take tasks at any level and decompose them—divide them up into pieces—to see the tasks at greater and greater levels of detail" (73).  Everything will be made distinct so that everything can be fixed.  Improved. Profitized.  Inefficiency will be removed.  

Whether you are novice, advanced beginner, competent performer, or expert, if your process is idiosyncratic, it will be analyzed and, eventually, reconfigured.  Maybe not this time round.  But the next software release will fold you into the efficient whole.

Miller ultimately discards the classifications, or perhaps tries to out-classify the old classifications by proposing a merger of some of the old oppositions: Aristotle's techne, joining description and prescription, theory and practice (22).  Finally, a third option to "this" or "that," "here" or "there."

I don't mean to upset Kinneavy.  Part of me wants to classify Plato as Narrative, Miller as Evaluation, and leave Classification to the others.  But that box won't do.  Modes tend to spin.  I agree that we approach subjects usually through a single side, a single door, a single fixed point—as when a writer decides to write a story, a review, a biographical sketch, etc.  But as Frank D'Angelo argues, we often fall under the sway of non-logical modes as much as logical modes.  We may enter through one side of Kinneavy's box, but we swirl around, up, down, out the other side. 

There is a power in inefficiency.  There is something fun in failing to divide.  There is revelation in de-classification.