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Paying Housewives

Wait, you say, we are talking about legitimate, blue and white collar workforce here, not in the third world. I pose that yes, male-dominated power networks are still in place, but pay discrepancies and difficulty of advancement still experienced by women in this country are mostly the result of automatic, unconscious bias, in the form of unquestioned assumptions about ability and psychological stability, as well as the usual fears about providing costly leave for childbirth and childcare. Try to think of it in terms of the infamous "trickle down" theory, except that what is trickling here is the remnants of social inequality that we do not want to examine, because as I've said, we are not a nation of overly introspective folk, prone to self-examination, and we do not want our land of the free, and our patriotic values to be criticized. Consider the existence of the fields of cultural anthropology and sociology, in particular. What do you think they are doing in subsets of these fields? When I feel better and have more time, I can get you into some academic databases, and you can have a field day with avalanches of decades-long studies and reports on issues such as you discuss here. You can find plenty of evidence in the life's work of many an anthropologist, sociologist, and cultural studies researcher to support the existence of remaining bias in the paychecks of women and minorities. One might argue that progress has been made since the 60s and the intensification of the civil rights movements; no one who is serious, and without a strong ideological agenda, can effectively argue that such bias does not exist, socially and materially. Acceptance of the facts does not mean that you have to call yourself a sexist or a racist, or give up your pride or belief that we are better off in this country or have made some progress.
— May 12, 2009 5:33 p.m.

Paying Housewives

So this is also a big challenge of the scientific method--controlling the variables, and sorting out the randoms and the "noise." You make a good indirect point that multiple variables should be considered when reading any kind of data--unfortunately, I did not take any statistics courses, so cannot get down and dirty with them. I have never designed a complex experiment. But I think I can safely say that we do accept that circumstances of any kind of test or measurement are subject to human error. (Researchers of course also have their own biases toward outcome to sort out, but we should bracket that off for now, and not drive ourselves nuts). So, you ask, how is it that males get into more accidents, but I see that males appear to be better drivers (we need to qualify what this means, btw)? Well, you might want to consider, for example, that youth and testosterone levels make males more prone to road rages and to playing chicken with other drivers. The DMV and insurance companies are sure to do their research on driving while twenty-something and male. Tacit reinforcement of expectations of our cultural roles, such as we have discussed privately elsewhere, can play a huge part in how a male might handle a situation on the road versus how a female might handle it. It is clear that generally, twenty-something males are raised with a cultural injunction to be more comfortable with participating in or even causing confrontative situations. The very construction of one's identity as 'masculine' may be on the line. (I do not say “machismo” because it carries its own complex of ethnic and cultural identifications that would muddy the waters for us here). We (meaning all of us bloggers on this thread) should also keep in mind that we sit in a unique position of privilege, and it can be hard, I understand, to perceive how remnants of gender bias have been articulated and rearticulated in our social fabric, within along with adjustments to the economic front, social and sexual mores, ideologies of gender identity, education, and accepted practices around childbirth, childcare, within our major social institutions. Historically, women have been more easily exploited as a cheap labor force than men, and in much of the world this is still so. refried brought up sewing and manufacture. Have you ever heard of a sweat shop? Many of us are probably sitting at our computers wearing clothing made in a Honduran or Indonesian sweatshop full of female indentured servants, and imported by a chic American or Euro brand providing a more palatable "face" to us as consumers. They still exist here, though such manufacture concentrates heavily in third world countries.
— May 12, 2009 5:32 p.m.

Paying Housewives

Josh, I think in a lot of your examples there is a missing factor that makes it difficult for you to read and interpret statistics against your own experiences and anecdotal experiences you've gathered. Btw, remember my practical advice (which you echoed) to magicsfive about tending to read and build arbitrary significance into "signs" in the world around us? Such activity becomes unconscious, hence the knee jerk reactions and the reactionary’s typical position, and the formation of narratives of meaning about life that seem to feel "right" but are often really symptomatic of our emotional needs, or originating in unquestioned beliefs about ourselves and the world. We must also examine how we do this with our politics, with our social assumptions at large, with our private dealings with individuals in terms of complex interactions of perceived gender and sexual identities, racial and cultural identities, and levels of ability. I always ask myself, 'What's in it for you, SD? How does this opinion or impression automatically, unthinkingly uphold some larger cultural bias or superstition I am clinging to? What big and little narratives do I live by that might be shaken by considering or accepting this new information or paradigm?' And I do make a habit of asking myself these questions :) So this is also a big challenge of the scientific method--controlling the variables, and sorting out the randoms and the "noise." You make a good indirect point that multiple variables should be considered when reading any kind of data--unfortunately, I did not take any statistics courses, so cannot get down and dirty with them. I have never designed a complex experiment. But I think I can safely say that we do accept that circumstances of any kind of test or measurement are subject to human error. (Researchers of course also have their own biases toward outcome to sort out, but we should bracket that off for now, and not drive ourselves nuts).
— May 12, 2009 5:31 p.m.

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