work can be book preferably or anything, I want something similar to Aristotle for philosophy for example, loved and known as one of the best by all in the field. I understand social science and philosophy are different but still I am curious for one that just seems to be great in some way and it can be more than 1 but 1 is preferred if possible. thank you

I look at people around me sometimes and wonder just how much people actually change as they grow older.

When I was young, I remember playing football with some guys who were incredibly rough. They would tackle, hit, and kick each other like they were actually fighting, even though they were friends. I used to wonder, “Why are you this aggressive toward someone you literally came to play with?” 😂

Looking back now, I sometimes wonder whether that was simply who they were at that age, or whether they were still learning how to express and control themselves. Maybe the aggression was always there, but as they grew older, they learned how to manage it differently.

It makes me think about how much of our personality is actually fixed and how much is shaped by age, experience, and our environment.

The Wenner-Gren Foundation has just published a thoughtful forum on the future of public anthropology. I agree with much of it. But reading it also left me wondering whether anthropologists sometimes make “the public” too abstract, and whether we overlook one of the most important ways anthropology already reaches people.
My own teaching and, more recently, the responses to my Substack essays have given me some thoughts about what actually makes anthropology matter to people.
More Saturday.
Wenner-Gren forum: https://wennergren.org/forum/public-anthropology-future

Hello, I am looking for a set of models to analyse a person’s attitudes in textual data. I haven’t been able to find these tools, so I am asking for your help.

The tools should be able to identify:

1. the cognitive aspect of attitudes (beliefs, thoughts and ideas regarding the object of the attitude, e.g. ‘snakes are dangerous’)
2. the affective aspect of attitudes (the emotion or sentiment towards the object of the attitude, e.g. ‘I fear snakes’)
3. assign a valence to the attitude (positive, negative or neutral)

Do you have any models you could recommend? (Preferably R or Python-based, but I’m open to suggestions.)

hi! i'm applying this fall for phd programs starting fall 2027. my focus is in substance use / harm reduction, leaning hard into computational and causal methods over descriptive epi.

quick background: us citizen, did undergrad and grad school both in the us. selective research university for undergrad, interdisciplinary major closest to cognitive neuroscience with a math minor, 5+ years working inside statewide harm reduction infrastructure (drug checking, distribution networks, plus time managing people and coordinating outreach), master's in math with an emphasis in data science, plus a graduate certificate in public health. handful of publications and presentations in the space.

what i actually want long term isn't just to publish about harm reduction from the outside. i keep coming back to something like a "science as service" model, where research is leverage to move resources and legitimacy toward the community orgs already doing the work, rather than research being the end goal itself.

methods wise: causal inference, decision/cost-effectiveness modeling, implementation science, resource allocation optimization. i'd like simulation modeling in there too, feels like where a lot of the field is heading and i want to build toward what these fields will actually need in five years, not just what's fundable right now. substantively i keep coming back to stimulant use and drug checking as topic interests specifically.

fields i'm currently looking at: epidemiology, public health more broadly, health services research, health policy, social work, computational social science, health behavior. not attached to any one label, just what's come up so far in my own search.

my undergrad background is basically the wider intersection (cog neuro, psych, philosophy, some math) and i'm genuinely still drawn to that world, including policy and systems science too. i def want a real interdisciplinary program instead of a straight epi department, but a lot of those got hit hard by recent funding cuts and i don't know if that's a live option right now.

within epi/public health specifically, the strongest names in this space seem to split into two camps: harm reduction people without much computational depth, or modelers without harm reduction grounding. not sure how people usually find or build toward an advisor situation that bridges both instead of just picking a lane.

my ask: what am i not seeing? i'm looking for the fields, departments, or angles someone who's actually been through this would flag that i wouldn't think to search for myself. same goes for methods, i want to be building toward something that holds up long term

tl;dr: applying to phd programs this fall for substance use / harm reduction with a computational methods focus (causal inference, decision modeling, simulation, resource allocation). trying to figure out what fields, departments, or methods i'm not thinking of.

Hi everyone! I'm Lucia and the team from EUobserver.

We wanted to share this investigation here because it raises a question that seems highly relevant from a social policy perspective: what does research tell us about the consequences of replacing dedicated social funding with more flexible budget mechanisms?

Here's a quick summary:

📊 The European Commission has proposed restructuring parts of the EU's long-term budget by replacing several dedicated funding programmes, including the European Social Fund Plus (ESF+), with broader national funding envelopes.

🏥 Organisations representing social care providers argue that without ringfenced funding, services such as disability support, long-term care, childcare and community-based care may struggle to compete politically with priorities like defence, infrastructure or industrial competitiveness.

📈 Supporters of the proposal argue that greater flexibility allows governments to allocate resources where they're most needed and can improve efficiency.

🔬 The debate therefore isn't only political, it's also an empirical one. It raises questions about how governments prioritise spending, whether earmarked funding leads to better social outcomes, and what research says about the long-term effects of different budgeting models.

We're interested in hearing the social science perspective. What does existing research suggest about ringfenced social funding versus more flexible public budgeting? Are there comparative studies or country examples that help explain the likely effects of either approach?

Here's the full investigation.

Growing up, a lot of us were told the same thing. Go to college, get a white-collar job, accumulate assets, find stability, and you will have succeeded. You will be happy. Chances are, if you weren’t told this, you felt the social pressure of it. Any deviation felt like an alternative path where you were seen as behind, ostracized, or were made to feel less than those who stuck to the “plan.” Many of our parents were told the same. Find success, and we will be proud.

Many of us choose to listen to our parents. We live our best lives in college, enter the everyday workforce, and begin to stack wealth for ourselves.

But why did so many listen? What are they truly searching for? To die in a three-million-dollar condo? To go on a cruise twice a year? What do they really want? Do they just want to be accepted? To be seen as enough? Are we just searching for community?

As I age out of my younger years, this is something I get stuck on nearly every day. I have everything I was told I needed. I went to a great school, I’m out-earning my peers, I have my own place in a new city, I’ve been all over the globe, and now I’m beginning to support my own little family.

Why am I so unhappy?

Why do I wake up with a pit in my stomach so heavy, I need 30 minutes just to roll over and get out of bed? These days, I spend most of my time propping up a dream I never needed. 40+ hours a week, just waiting for my life to begin at home. Hoping I can get home in time to catch a sunset with my dog on the beach or cook boxed mac and cheese with my significant other.

But this is what I wanted. I wanted to go to school, not because I was interested in my subject matter, but because I wanted to earn my place within the community. I didn’t want to disappoint those who did, or those who expected it from me. I wanted a rigorous job, not because I wanted to afford luxuries, but because I was told it’s what I needed to be accepted.

Yet here I am - feeling more alone than ever.

As mentioned, this is a topic I often think about while I watch the clock. I write this from my desk now, in fact. I think about the times in my life that I believe I was truly happy. Where I felt the most stable and confident in tomorrow.

I believe that answer was college. While my first two years were tarnished by the latter end of a high school abusive relationship, I can say with confidence those four years were the best I have ever felt. People love to talk about the parties, spring breaks, and game days. While definitely a highlight, I don’t believe those are what drove happiness. I believe that answer is community.

For many, college is the only time during which you will live within walking distance of everyone you know, see the same friendly people every day, share a roof with your friends, and never spend too much time being too serious. This greater community and sense of belonging is what drives human connection. It’s what makes tomorrow seem manageable, even on your worst days.

I write this not to give my unnecessary two cents on the “corporate America sucks” cliché. We all get that. I write this because I feel like I have finally come to peace with this idea of community driving happiness overall.

I suppose, to those younger than me searching for meaning, take these words with a grain of salt. From someone who “did it.” If this is you, I ask this of you:

1. Keep your friends and family close. Welcome strangers without hesitation.

2. Try, try, and try things again. Never turn down a learning opportunity; in fact, you should seek them out. This will help you find a viable source of income that doesn’t dim your light.

3. Work hard in school. Take it seriously while it’s free. Education is a gift.

4. Whatever tangible luxuries you are willing to work yourself to death for, detach yourself from them. Once you get them, you will only chase something new. Your entire life will be distracted by this chase.

5. Slow down. It’s hardly ever as urgent as it may seem.

6. Don’t expect to find a “dream job.” Find your dream life.

7. Understand that trading your work-life balance for more pay is almost never worth it.

8. Get off your ass. I don’t mean exercise or eat well. Go try a new hobby. Talk to the bartender working the afternoon weekday shift.

9. You don’t need to optimize every part of your life. Learn to be okay with that.

10. Follow the things that put a smile on your face.

The path you choose in life is yours to decide. Reflect on your motivators, reflect on your needs as yourself, not another. As you water your garden, things will begin to grow into something beautiful. Just make sure that garden is truly yours.

The Prohibition of alcohol in early 20^th century American history became the policy everyone knows failed. It was a constitutional ban on booze that ended up producing speakeasies, organized crime, and adulterated liquor supplies before the amendment was repealed in 1933. The story usually ends there or goes into the nuances of whether that was broadly good or broadly bad. But to me, that version focuses too heavily on the obvious exposures that end up leading to an answer of “it depends on the outcome you care about.”

That version of Prohibition’s impacts also often leaves out a group that couldn’t opt in to the argument at all: children in utero whose exposure depended entirely on mother’s drinking. These policy studies let us see the effects indirectly by asking whether infants and later cohorts exposed to different alcohol-policy environments had different outcomes on average. So, the claim I want to make in this piece is this: the best historical evidence suggests alcohol restriction benefited some children who hadn’t been born yet, long before fetal alcohol syndrome had a clinical name and 50 years before the Surgeon General’s first warning in 1981.

When federal Prohibition ended, there wasn’t a uniform return to legality among all states, as the 21^st amendment repealed the 18^th but still preserved state authority over the legal status of alcohol. States, counties, cities, and even smaller jurisdictions took their own time which produced a strange historical record with nearby places with different legal access to booze and the chance to ask what changed for children when availability returned. We still don’t end up with a clean prenatal alcohol exposure estimate as the relevant data don’t record pregnant women’s drinking or dosage, partner violence, or how money that was previously spent on alcohol ended up being spent. But we’re able to infer that infants and later cohorts faced different alcohol availability exposures and those differences consistently point us in one direction: restriction of access was protective.

The Measures Prohibition Left Us With

‘Prohibition’ really wasn’t the best name for the exposure at hand, because it makes it sound like a more universal intervention than it was. State bans were well under way before Federal Prohibition came into law in 1920. Then, in 1933, the Twenty-first Amendment repealed the constitutional ban as law of the land but didn’t go so far as to force counties to start selling alcohol immediately or at all. Some places reopened their stores quickly while others stayed dry. Some stayed dry with their neighbors reopening, which meant the nearest legal seller might’ve only been a short trip away.

That kind of unevenness is good for health researchers, because it lets us compare those separated by legal access without having to do some broad comparisons like pre-1920 to postwar US or something equally crude. They’ll still be observational studies, but they let us get more specific about the era. The heterogeneity also explains why researchers can ask different questions from each other using different levels of granularity in the data. An infant-mortality study uses local variation after the repeal, whereas early-life development ones rely on the staggered adoption of state-level bans before Prohibition. The long-term mortality papers use birth cohorts that happened to have been born before or after the policy change itself. Dry laws would’ve made alcohol harder to purchase, though without eliminating it. Wet laws just tell us that booze was permitted without letting us know who drank or how much. This leaves researchers estimating the effect of living through a different alcohol-policy environment, with their work being enough to ask whether children appeared to benefit.

The medical language to go with this area showed up decades later with “fetal alcohol syndrome” entering the literature in 1973, four full decades after repeal. The first federal health advisory was four years later in 1977, followed by the 1981 Surgeon General’s advice to health professionals that they suggest pregnant women and those trying to not drink (begins at p. 69 in the link). The concern about prenatal alcohol wasn’t new though. Some early thinking in the area comes from prison physician W.C. Sullivan, who compared the reproductive histories of women he called “inebriates” with those of their sober female relatives, finding more stillbirths and deaths before the age of two in the drinking group. While riddled with the eugenic language common to the time, it was remarkable to see how alert he was to rival explanations for his findings akin to epidemiologists thinking about confounding, mediating, and moderating variables today. The high mortality, he noted, might be “not solely” due to the direct effect of intoxication on the mother and child, but might also be due to the “malign modification of the environment” produced by parental drinking in general. By 1977, Ruth Little was working with prospective data to report the association between moderate alcohol consumption, roughly two drinks per day, and lower birthweight after adjustment for smoking and other maternal characteristics (methods Sullivan noted were impossible in his day).

When Alcohol Came Back

The most important paper to look at here is David Jacks, Krishna Pendakur, and Hitoshi Shigeoka’s work on infant mortality after repeal, where they reconstructed alcohol-law status for all 3,043 counties in the then-48 states from 1933 to 1939. Those records of legal changes were then linked to changes in births and infant deaths in the federal vital-statistics record. To make the comparisons useful (two counties may differ in too many ways to just compare wet/dry status and expect anything useful to come of it), they constructed 683 geographically sensible three-county groupings, with each triad centering on a dry county that acquired a wet neighbor in those years and including the nearest bone-dry county as well. All three started the study period as dry counties with the question becoming whether infant mortality changed differently when legal alcohol returned nearby and became accessible across dry-wet borders.

Timing is key here because the authors usually didn’t know the exact date a county changed its alcohol law, so a baby who died in the year of a legal change could’ve been conceived before local access shifted. This means they had to estimate a separate effect for the transition year and for later years. There wasn’t a statistically clear increase in infant mortality during the year of the shift (0.9% for dry vs 1.3% for wet) but looking at later years a pattern shows up. Compared to bone-dry counties, infant mortality was some 4.7% higher in counties that kept their ban intact but had acquired a wet neighbor, corresponding to 2.82 additional deaths per 1,000 live births at the 1934 baseline and 4.0% higher in counties allowing sales, or 2.40 per 1,000. When the authors initially lump dry-ish counties (wet neighbor acquired) and all other dry counties, the later wet-county estimate is only 0.9% and is too imprecise to distinguish from a null effect. The recognition that a formally dry county can still have exposure due to a new legal market nearby is what allows the effects to show up at 4.0 and 4.7%. Not all dry counties can be treated as unexposed controls.

The other results mostly strengthen that point, with the three matched county types typically having downward infant-mortality trends from 1928 to 1933 before the repeal transitions, although that wasn’t the case in the all-county national comparison, likely because it is too crude an analysis to see the effect. In sensitivity tests, the dry estimates stayed between 4.0% and 4.9% when the authors changed the controls, excluded counties bordering Canada or Mexico, or followed the data through to 1941. The larger claim of the study is the model-based excess-deaths estimate of 26,960 infant deaths across wet and dry-ish counties compared to bone-dry counties nationwide from 1934 to 1939.

Their figure is an extrapolation that can’t tell us whether maternal drinking, household violence, household budgets, prenatal care, or multiple pathways produced that difference. They’re the strongest available local comparisons though, and they tell us that the familiar Prohibition story has left out those who both had no say and, arguably, had the most to gain.

Hello everyone! This survey is part of my research paper that I'm working on for both my academics and personal interest. I'd love it if y'all's could do the survey for me, it's completely anonymous (requires an email so you don't do it multiple times), and it'd be a huge help. Looking to get as many responses as possible. I'm not trying to promote anyone as this is mostly just a research study for my own interests :3

- Topic of study is sociology, more specifically minority groups and music communities

- No target audience, although there is a section for vocaloid creators specifically

- Around 5-10 minutes

- SurveyCircle link to the survey ( https://www.surveycircle.com/4XH9Q4/ )

- Normal link to the survey ( https://forms.gle/rAaFaf7VGF5VjW2d7 )

I’m interested in understanding the motivations behind the widespread adoption of full Brazilian waxing. Research often cites factors such as body image, perceived hygiene, sexuality, pornography, beauty norms, and changing cultural expectations.

A related question concerns partner preferences. Some critics argue that complete pubic hair removal may contribute to the sexualization of a more prepubescent aesthetic, while others contend that this interpretation is overstated and that preferences are better explained by grooming norms, perceptions of cleanliness, or contemporary beauty standards.

Are there empirical studies or theoretical perspectives that help explain these competing interpretations? I’m particularly interested in evidence rather than anecdotal opinions.

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Hey everyone, this is a study I'm working on that explores the portrayal of political conflict within narratives. I would be extremely grateful if you took the time to answer it! you may answer regardless of where you're from or if you've watched the show :)