UNIVERSITY
OF NAIROBI
DEPARTMENT
OF SOCIOLOGY
CSO
405: SOCIOLOGY OF WORK AND INDUSTRY
SEMESTER: May – August 2016 [Regular & Module II Programmes]
"A measurement tells us about a property of something. It might tell us how heavy an object is, or how hot, or how long it is. A measurement gives a number to that property. Measurements are always made using an instrument of some kind. Rulers, stopwatches, weighing scales, and thermometers are all measuring instruments. The result of a measurement is normally in two parts: a number and a unit of measurement, e.g. ‘How long is it?... 2 metres."The measurability rule is anchored on the above conceptions, and so requires that the variables around which the researcher intends to collect data should be measurable, or susceptible to acceptable ‘measurement’ (Leedy, 1980: 46)[1]. This is easier done in the natural sciences than in the social sciences; in quantitative studies than in qualitative. Still, one must, in the social sciences too, endeavor to quantify, measure and evaluate. Indeed, the guiding principle of the measurability rule -- its corollary, in other words -- is this: "What can be measured must be measured." Thus, not measuring what can be measured is not an option allowed anyone.
"By measuring or manipulating individual constructs, relationships between constructs are studied and substantive hypotheses about these relationships are tested. The very notion that numbers can be assigned to attributes of people, objects, or events is presumed on being able to study attributes or constructs separate from other constructs. After all, measurement relates to rules for assigning numbers to attributes of people, objects and events. [But] this is not the case for many phenomena. A complex network of constructs may influence a phenomenon and may not be separable into individual constructs for purposes of measurement."Measurability procedures implemented in qualitative -- that is, 'non-numerical' -- research attempt, not always successfully, to overcome or circumvent such intractables as Viswanathan has pointed out. These procedures include, for example, “comparative judgement (arranging factors in a hierarchy of importance)” or “scaling (correct versus incorrect responses to a given set of questions)” (Leedy, 1980: 46). Other ‘non-numerical’ strategies that have been used, according to Worsley (1992: 113)[2] include: “careful classification[3], organizing and combining of field-notes [which] requires patient checking and cross-checking and the application of systematic techniques.” But he acknowledges that “numerical methods are sometimes applied to field-data too” (Worsley, 1992: 113). Indicators are often used as proxies/surrogates for more fuzzy or abstract concepts, such as status (Worsley, 1992: 96). Such indicators are inevitably numerical.
"Uncertainty of measurement is the doubt that exists about the result of any measurement. You might think that well-made rulers, clocks and thermometers should be trustworthy, and give the right answers. But for every measurement - even the most careful - there is always a margin of doubt. In everyday speech, this might be expressed as ‘give or take’ ... e.g. a stick might be two metres long ‘give or take a centimetre’."