*: This is partly plagiarized, but I regrettably lost the reference. Although it is nothing terribly new, I think it is still worth bringing to a higher level of consciousness every now and then. Any disagreements?
[Claudio, On the same subject, here is a quote whose author I also do not know:
“If you torture multi-variate data sufficiently, they will confess!” Cordially, Joe Hannah]
Statistics create subjects; they tell stories and shape cultures.
Over the past five decades, development practitioners have prided themselves on successfully creating more sophisticated ways to measure and compare. Statistics have become crucial, if not the most crucial of, development tools.
They describe, measure and help to build the arguments in favor of, or even against, development issues. (For example, as somebody jokingly said, “smoking is a major cause of statistics”).
Statistics, we are told, reflect economic and social characteristics; they have the power to focus awareness on a range of problems, deficiencies, challenges and improvements.
Of all the development tools, it is clear that statistics play the central role in constructing power and knowledge.
However, statistics are often used unknowingly (?) by development experts to further entrench the (prevailing) development discourse. The problematic, potentially biased nature of the statistic in development work is given little credence.
One of the cruxes is in the choice of indicators; it always embodies certain values about what information ‘counts’ (- “whatever the cakes we bake are the ones we will have to eat”). For instance, when choosing which data are collected to determine the type and extent of a given health problem affecting a population, Human Rights principles and norms can be considered or disregarded. The resulting statistics will tell a different story altogether.
Further, decisions on how to disaggregate data (by age, gender, socioeconomic, ethnic or other group) also have direct influence on the policies and programs that are put into place.
While being comforted by the statistic, we remain unaware of how central the use of statistics can be to the politics of representation. Statistics ultimately is a political technology which can create a reality that is understood as factual and as a translation of the truth.
We thus have good reasons to be skeptical (or at least inquisitive) about statistics; after all, it is notable that the seventeenth century term for what is now called statistics was “political arithmetick”.
Claudio Schuftan, Saigon
schuftan@gmail.com