by "turnaround" he meant the dems regaining the lead over trump after ditching biden. They'll want to keep that momentum going and avoid bad press, so they might be more willing than usual to meet some demands of pro-Palestine protesters
iie
the ambiguity of "is my post reactionary, and/or just stupid, and/or no one actually read the paper," where each warrants a different response—do I self-crit? do I shrug because "everyone posts cringe sometimes"? do I defend the paper but risk doubling down on whatever might be reactionary or dumb about it?—is weirdly socially stressful even though I can handle the individual possibilities
Depends on how you define "America." After you change the government, economic system, culture, and name, it starts to be a Ship of Theseus thing.
The only question left is the borders, but "in a communist world" borders are less important. We might even have overlapping voting regions and sub-regions like a big complicated Venn diagram, depending on the issue at hand. Maybe everyone in the Rio Grande watershed votes on Rio Grande-related issues. If your farming community straddles the watershed divide, maybe half your neighbors vote on Rio Grande-related issues and the other half don't.
I don't see a reason to keep the current borders of America, but also, I'm not sure what the borders will even mean.
psychological impacts of upbringing and the way parents assign names
and the psychological impact of whatever subconscious stereotypes people have about your name—like "chad" being a jock name, for example
people get the same result when figuring out if face shape is associated with criminal behavior.
my embarrassment grows lol
it's literally looking at skull shapes
only adults, not children, showed any face-name correlation, according to the authors. That would rule out skull shape—for whatever that's worth.
I'm not trying to double down on this goofy study I saw on youtube. I'm just feeling embarrassed and defensive that everyone is shitting on my post. I'm subscribed to a guy named Anton Petrov who summarizes new papers, and I saw this video title and thought "Wait, what?" but when I watched it it seemed to have a plausible angle.
First or last? Did they test each separately?
They said "given name" which usually implies first name
Did they account for factors of name popularity and environmental upbringing during specific periods of time?
looks like it *or at least, they controlled for period of time:
Thus, we ensured that the filler names came from the same pool as the targets and belong to adults of the same age and demographic as the targets.
How is it a phrenology study?
The hypothesis would be that your name can affect your personality, which can then affect your habitual facial expressions, hair, and makeup.
I once had an art teacher whose last name was Doart, pronounced "do art"
That figure is about people guessing other people's names—they guess adults' names more often than they should, although still not that often, but they don't guess childrens' names more often than random chance
They're talking about haircut, glasses, and makeup, not bone structure and fat distribution.
Obviously not bone structure. I don't know why that would constitute a lede to be buried.
But they're not just talking about haircut, glasses, and makeup either. They found effects even for grey-scale images with hair cropped out of the photos—see the quote below. Other studies have found that a person's personality can affect their face—probably through the facial expressions they tend to make. If your name might affect your personality, and your personality might affect your face, it seems reasonable to investigate if your name can affect your face. The researchers provide multiple lines of evidence suggesting this might be the case.
Across the machine learning studies (Studies 3 and 4B), while the facial images included facial accessories (e.g., glasses, etc.), the images were cropped around the face itself such that hardly any hair was included. Prior to feeding the images into the neural network, we preprocessed the facial images using several steps to ensure accuracy and consistency. Initially, OpenCV’s deep learning face detector, which is based on the single shot detector (SSD) framework with a ResNet base network, was employed to crop faces from the images. All cropped faces were manually verified to ensure the accuracy of the detection. Subsequently, the images were converted to grayscale, normalized to have pixel values between 0 and 1, and resized to 128128 pixels. This preprocessing approach is supported by several studies that highlight the importance of consistent face detection and preprocessing for improving neural network performance (30–32).
Really interesting article about him, thanks for sharing. Apparently he was an actor, painter, and three-time prison escapee with multiple aliases.
The Guardian article mentions some more stuff about his past: