my pronouns are he/it because you're meant to he/it me with your car #vehicularmanslaughter

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@freshfishman
my pronouns are he/it because you're meant to he/it me with your car #vehicularmanslaughter
they should allow you to report posts for being gauche or passé
tch... so it's an alliance out of necessity, huh...?
Look I love unconditional devotion love stories as much as the next person, but there's really something so deliciously raw about conditional devotion.
I have served you and I have loved you for decades, but I will not give up my principles for you. You cut out part of my heart and took it with you down that path that you insist on walking, but you walk it alone. Even when the bleeding, gaping hole you left in my chest kills me, I will not follow you.
me everytime one of my seemingly non-specific homoerotic text posts breaks containment
Fuck moonâs taking poison damage
DONT ask why corvid isnt wearing a shirt bc the answer is embarrassing. (i forgor to draw it)
Splatoon Raiders epilogue scene.
This is my contribution to Splatoon worldbuilding.
the phrase "but i didn't mean to!" in the context of causing harm is kind of redundant to me, because almost nobody means to cause harm. most of us just want to do the right thing. and i don't mean that in a wishy-washy "oh, we're all good deep down" way, i mean that even people who regularly do the most heinous shit imaginable will have a way of justifying it to themselves. the world is not populated by hollywood sadists and psychopaths.
actually i have been thinking about this some more and i want to add on to it:
abuse in caregiving professions (like teaching or nursing) is not solely a result of power dynamics. it's also because people who go into those professions often have a idea of themselves as Good People, and are consequently incapable of recognising or acknowledging when they've hurt someone else. instead, they mentally put 'people who have inconvenienced me' into the Bad People box so they can freely abuse them while maintaining their moral high ground.
i read ross greene a lot when i was working with "difficult" or "behaviourally challenged" children. his refrain is "kids do well if they can" - meaning, in short, that most kids act out only when the demands of a situation exceed their capabilities. punishing them for this is not only cruel but also completely pointless, because they also don't want to be doing what they are doing.
a teacher who believes that there are two categories of people - Good People who Mean Well, and Bad People who Cause Problems on Purpose - is not going to see it that way. they're gonna put themselves in the first category, and the misbehaving kid in the second category. and once they have effectively depersoned the child and placed themselves on a pedestal, the world becomes simple again. because abuse is something that only Bad People do.
playing stupid games but im really bad at them so im not even winning the stupid prizes
in retrospect it's pretty funny that the most used computer port for many years just completely sucked shit to the point of there being normie memes about it
we as a society lived like this for years and years
I mean when your biggest tech issue is "takes an extra 10 seconds (at most) to plug in if you're not paying attention" that's pretty good! Imagine if you had a printer and the printer's biggest problem was that the paper took a few tries to insert into the tray. You'd want to fuck that printer.
I'd want to fuck that printer.
it really is quite bad for your military to have an image of itself as a warrior class. what you really want is for your soldiers to think of themselves as boring professionals who will fill out a report form if someone gets a little too warrior ethos out there
â James Baldwin, They Canât Turn Back
*monkeyâs paw gives me a biiig thumbs up*
I had a lot of/still have some vestigial arrogance about quantitative methods over qualitative ones, probably in a combination of scientific misogyny + STEMlord superiority. But doing regression analysis and quant-heavy data analysis makes me realise more and more that you can justify basically any claim with numbers, and that you can construct your research in such a way as to output the numbers you want. which does not mean that all data are made up or that quantitative knowledge is all false. I think stories about scientists straight up inventing numbers or fudging experiments on purpose prove that there is a real difference between fraudulent and non-fraudulent research. but those data must always be narrativised & are always already narrativised. The act of presenting numbers itself is doing some of that narration because youâre already arguing that these numbers are worth presenting
People in the notes are rightfully pointing out common issues with data manipulation and pre-loaded conclusions in scientific research (i.e., the academic version of asking "so, how often do you beat your wife?" and so on), but I should have clarified that I'm not really talking about that. I'm talking about completely legitimate, above-board scientific research.
For example, I've had students ask me (in good faith) how it was possible for international medical bodies to report different counts of COVID-19 cases during the early years of the pandemic. And one of the answers is that you need to first define what you mean by a "COVID-19 case." Do you include self-reported incidences? Waste water data? Geo-fenced social media posts about people complaining about their coronavirus symptoms? Federal estimates? Hospital data? How do you compare countries/territories/substate entities with mandatory reporting mechanisms vs countries/territories/substate entities that rely only on voluntary self-reported cases? And what combination of these do you use? How you construct what you mean by "case" is going to impact the outcomes you report. These different counts of COVID-19 cases can all be true simultaneously, not because numbers are made up, but because they all come out of different methodologies that can be equally valid.
And this is true across all science, not just social science. Bill Clinton said it best lol: "it depends on what your definition of the word 'is' is." This feels obvious when you look at scientific research that uses "skull measurements" as their object of analysis - the concept itself is white supremacist, regardless of how "sound" the research is. But even something as apparently self-evident as a COVID-19 case still requires a definition, and how you define your variables is necessarily going to impact how the research goes and what conclusions are drawn.
These definitions are always embedded in political & social assumptions. And again, this does not mean that science is all made up or nonsense or whatever. There is a widespread fetishism of "objective knowledge" that is itself ideological - the idea that knowledge can be divorced from all historical and political contexts, that you can scrub bias from research and simply report the facts. Valuable, well-supported, well-constructed scientific research is always embedded in these contexts. Not just as a result of researcher assumptions, but of the material context it exists in - what research resources are available, how & what research gets funded, the academy's relationship to the state & non-government bodies that both provide data and use that research to inform policy, the historical relationships universities often have with settler-colonialism and imperialism that give them access to "foreign" research subjects, etc etc etc.
So my overall point (which I didn't communicate well) is that data can always say what you want to some extent, for good and for ill. And research results (at least in my experience) tend to surprise you in ways that require explanations, which themselves can be fully justified, but again, exist within many different contexts that influence how you interpret them - and not just the results themselves, but your own surprise at your results