Ideally this would be true, but it’s not. Women and men are both oppressed by gender roles,
I agree that any meaningful definition of oppression must apply to both genders. I’ve tried to imagine definitions of “oppression” by which only women are oppressed, but they must be extremely contorted. It’s impossible to define “oppression” as only effecting women without being blind to certain systematic harms that happen to men, or without trying to define it that way.
but women get the worst of it on net.
I’ve heard this claimed, but I’ve always wondered what this comparison means. “The worst of it on net” implies some sort of aggregation function for oppression. What is this function, and what are the units of measurement?
To make a quantitative comparison, your quantities must have the same units. That’s difficult when attempting to compare social harms. If someone asks you, “what’s worse, men being considered more dangerous to children, or women being considered less legitimate in positions of authority in the workplace?” the answer is “what a stupid question… those things have different units.”
Maybe there is some magic oppression function, and someone somewhere has completed the philosophical tour de force that would allow us to meaningfully compare oppressions of different groups in a quantitative manner.
Or maybe the emperor is wearing no clothes, and the people who advance this argument are being biased and self-serving, just like any political advocacy group.
nawitus was talking about an ideal split of resources to aid each gender. Since he proposed a 50⁄50 split of resources, he might well believe that there is an even split of “oppression,” but you’d have to take that up with him.
I’m not sure it makes sense to choose any split, because shitty things that happen more often to women are measured in different units than shitty things that happen more often to men. We would need some way to convert those quantities into the same units to make a comparison. Even in an inconvenient enough world, I’m not sure you can make a split of a quantity measured in feet and a quantity measured in pounds.
You have $100. You must only spend it in some combination on a) issues that are clearly specific to men or b) issues that are clearly specific to women. Which do you pick?
Even less convenient world:
I, the Grand High Poo-Bah of the World, have just appointed you Director of Spending on Gender-Specific Oppression. I have outlawed all charitable spending on gender-specific oppression not routed through your office. I have given you a budget equal to the current spending on gender-specific oppression, or to a randomly selected figure. If you do not pick how to spend it, I will take it back and spending it on professional baby-punchers. How do you spend it?
Any kind of moral ontology is totally irrelevant in a real-world situation where you actually have to pick.
Under circumstances like that I would start by requisitioning some census data from the Director of Figuring Out What Gender Actually Is, to determine the number of males, females, and misc/other. Initial budgeting would assume a uniform per-capita distribution of gender-specific oppression.
Then I would do some surveys, focus groups, statistical analysis of written complaints, and so forth to identify the main problems in each category. Naturally, information-gathering for a specific gender’s problems comes out of the budget for that gender, although there might be some post-hoc fiddling around if a survey intended to address one issue provides unexpected insights outside it’s category.
Once the issues are identified, I would set up teams of economists, anthropologists, etc. (mixed specialties in any given team) for in-depth analysis of causes and possible solutions. Each problem gets more than one team, each team is expected to come up with a predictive model of the problem before anyone proposes solutions, and then to have multiple possible courses of action with cost/benefit analysis for each, including the null option and at least one option which is completely stupid.
After the possible courses of action are laid out, each team is handed the full analysis of two or more interventions proposed by other teams and assigned the task of mapping out how those courses of action might interfere with each other. Bonus points for spotting errors or oversights in the other team’s analysis, or ways that multiple interventions could be cost-effectively combined. The result is one or more new proposals which are then added to circulation.
Eventually, a few ‘gems’ would emerge: plans with exceptionally high cost/benefit ratios, exceptionally low risk of negative externalities, or that would otherwise be unconscionable to avoid acting on. Each of these gets as much funding as necessary, up to… let’s say about 80% of the relevant category or categories.
After the gems are polished off, either to the point of diminishing returns or concern over too many eggs in one basket, the remainder of any given categorical budget is distributed between contingency planning against the possibility of flaws in the ‘gems,’ the various second-string plans (with an eye toward political expediency), and various long term concerns such as follow-up studies.
Yes, but it of course depends on some form of inter-comparability of the costs and benefits of different approaches. Such a tool for comparison should enable you to, with all the analysis that you’ve laid out here, come up with a highly accurate estimate for % of oppression of men vs women vs. other. (For instance, you would probably find that oppression of other is higher than either oppression of men or oppression of women.)
If the various approaches are government programs, costs and benefits could be compared in terms of dollars spent, dollars of taxpayer benefit produced (if someone would have been willing to pay to change, say, a dress code, and obtains that benefit for free, that’s an IPED dollar-value benefit to them) and approval-rating percentage points.
I would expect gender-related oppression of misc/other folks to be higher, in per capita terms, than either men or women, yes. For one thing, earlier stages of this very discussion glossed over them altogether. However, I would also expect that quite a bit of that oppression is not strictly gender-specific, and avoid initially allocating disproportionate funds to that category out of respect for the limits of my department’s mandate.
Presumably there is a Director of Spending on Surgically Correctable Birth Defects or somesuch who would legitimately have at least partial jurisdiction over transsexuality, and a lot of individual citizens who are oppressed for reasons only tangentially related to ambiguous gender. I would of course want to coordinate with other departments to clearly delineate who is responsible for which edge cases and to what degree, erring on the side of too much overlapping coverage, if for no other reason than because broad prohibitions on charity might leave some unaccounted-for micro-minority with absolutely no legitimate recourse.
Naturally, if subsequent investigation reveals the misc/other category to have more low-hanging fruit, or useful externalities on a larger category, that changes things. Evidence based reallocations were explicitly included in my proposal.
So I don’t see why we disagree.
I suspect it’s a matter of technicalities rather than fundamental goal disconnect. If I want to keep the Baby-Punchers Local #403 from getting a new pool table in their rec room, I’ll probably need to come up with some plausible-sounding budget allocations today, not in six-plus months after all the research is already done and paid for.
No actually the reason we disagree is that I was having an argument with HughRistik and asked him a question as a method of argument, and then you answered the question having already internalized my stance and thereby saying a bunch of true but irrelevant stuff, and then I didn’t bother to look up his name and verify that you were different people.
I agree that any meaningful definition of oppression must apply to both genders. I’ve tried to imagine definitions of “oppression” by which only women are oppressed, but they must be extremely contorted. It’s impossible to define “oppression” as only effecting women without being blind to certain systematic harms that happen to men, or without trying to define it that way.
I’ve heard this claimed, but I’ve always wondered what this comparison means. “The worst of it on net” implies some sort of aggregation function for oppression. What is this function, and what are the units of measurement?
To make a quantitative comparison, your quantities must have the same units. That’s difficult when attempting to compare social harms. If someone asks you, “what’s worse, men being considered more dangerous to children, or women being considered less legitimate in positions of authority in the workplace?” the answer is “what a stupid question… those things have different units.”
Maybe there is some magic oppression function, and someone somewhere has completed the philosophical tour de force that would allow us to meaningfully compare oppressions of different groups in a quantitative manner.
Or maybe the emperor is wearing no clothes, and the people who advance this argument are being biased and self-serving, just like any political advocacy group.
if they are non-intercomparable, you cannot justify an even split.
Where did I make an even split?
You responded to Normal Anomaly, who responded to nawitus, who suggested an even split. It was a reasonable guess that you supported it.
The general version of my argument is:
You have to choose SOME split, given an inconvenient enough world. Which do you pick? How do you justify it?
nawitus was talking about an ideal split of resources to aid each gender. Since he proposed a 50⁄50 split of resources, he might well believe that there is an even split of “oppression,” but you’d have to take that up with him.
I’m not sure it makes sense to choose any split, because shitty things that happen more often to women are measured in different units than shitty things that happen more often to men. We would need some way to convert those quantities into the same units to make a comparison. Even in an inconvenient enough world, I’m not sure you can make a split of a quantity measured in feet and a quantity measured in pounds.
Clearly some specifics are in order:
You have $100. You must only spend it in some combination on a) issues that are clearly specific to men or b) issues that are clearly specific to women. Which do you pick?
Even less convenient world:
I, the Grand High Poo-Bah of the World, have just appointed you Director of Spending on Gender-Specific Oppression. I have outlawed all charitable spending on gender-specific oppression not routed through your office. I have given you a budget equal to the current spending on gender-specific oppression, or to a randomly selected figure. If you do not pick how to spend it, I will take it back and spending it on professional baby-punchers. How do you spend it?
Any kind of moral ontology is totally irrelevant in a real-world situation where you actually have to pick.
Under circumstances like that I would start by requisitioning some census data from the Director of Figuring Out What Gender Actually Is, to determine the number of males, females, and misc/other. Initial budgeting would assume a uniform per-capita distribution of gender-specific oppression.
Then I would do some surveys, focus groups, statistical analysis of written complaints, and so forth to identify the main problems in each category. Naturally, information-gathering for a specific gender’s problems comes out of the budget for that gender, although there might be some post-hoc fiddling around if a survey intended to address one issue provides unexpected insights outside it’s category.
Once the issues are identified, I would set up teams of economists, anthropologists, etc. (mixed specialties in any given team) for in-depth analysis of causes and possible solutions. Each problem gets more than one team, each team is expected to come up with a predictive model of the problem before anyone proposes solutions, and then to have multiple possible courses of action with cost/benefit analysis for each, including the null option and at least one option which is completely stupid.
After the possible courses of action are laid out, each team is handed the full analysis of two or more interventions proposed by other teams and assigned the task of mapping out how those courses of action might interfere with each other. Bonus points for spotting errors or oversights in the other team’s analysis, or ways that multiple interventions could be cost-effectively combined. The result is one or more new proposals which are then added to circulation.
Eventually, a few ‘gems’ would emerge: plans with exceptionally high cost/benefit ratios, exceptionally low risk of negative externalities, or that would otherwise be unconscionable to avoid acting on. Each of these gets as much funding as necessary, up to… let’s say about 80% of the relevant category or categories.
After the gems are polished off, either to the point of diminishing returns or concern over too many eggs in one basket, the remainder of any given categorical budget is distributed between contingency planning against the possibility of flaws in the ‘gems,’ the various second-string plans (with an eye toward political expediency), and various long term concerns such as follow-up studies.
Does that seem reasonable?
Yes, but it of course depends on some form of inter-comparability of the costs and benefits of different approaches. Such a tool for comparison should enable you to, with all the analysis that you’ve laid out here, come up with a highly accurate estimate for % of oppression of men vs women vs. other. (For instance, you would probably find that oppression of other is higher than either oppression of men or oppression of women.)
So I don’t see why we disagree.
If the various approaches are government programs, costs and benefits could be compared in terms of dollars spent, dollars of taxpayer benefit produced (if someone would have been willing to pay to change, say, a dress code, and obtains that benefit for free, that’s an IPED dollar-value benefit to them) and approval-rating percentage points.
I would expect gender-related oppression of misc/other folks to be higher, in per capita terms, than either men or women, yes. For one thing, earlier stages of this very discussion glossed over them altogether. However, I would also expect that quite a bit of that oppression is not strictly gender-specific, and avoid initially allocating disproportionate funds to that category out of respect for the limits of my department’s mandate.
Presumably there is a Director of Spending on Surgically Correctable Birth Defects or somesuch who would legitimately have at least partial jurisdiction over transsexuality, and a lot of individual citizens who are oppressed for reasons only tangentially related to ambiguous gender. I would of course want to coordinate with other departments to clearly delineate who is responsible for which edge cases and to what degree, erring on the side of too much overlapping coverage, if for no other reason than because broad prohibitions on charity might leave some unaccounted-for micro-minority with absolutely no legitimate recourse.
Naturally, if subsequent investigation reveals the misc/other category to have more low-hanging fruit, or useful externalities on a larger category, that changes things. Evidence based reallocations were explicitly included in my proposal.
I suspect it’s a matter of technicalities rather than fundamental goal disconnect. If I want to keep the Baby-Punchers Local #403 from getting a new pool table in their rec room, I’ll probably need to come up with some plausible-sounding budget allocations today, not in six-plus months after all the research is already done and paid for.
No actually the reason we disagree is that I was having an argument with HughRistik and asked him a question as a method of argument, and then you answered the question having already internalized my stance and thereby saying a bunch of true but irrelevant stuff, and then I didn’t bother to look up his name and verify that you were different people.