Papers I Reread

Lena Carver

@latecheckoutlena1166

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These are the PDFs I end up reopening at 1:17 a.m. when I was allegedly just “checking one thing.” A little stats, a little psych, a little media theory, some econ, some computer science—basically the intellectual equivalent of watching game tape and director’s commentary at the same time. None of this is light beach reading, but every one of these papers has at least one paragraph that made me stop, stare, and mutter, “Okay, that’s annoyingly brilliant.”

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Papers I Reread — 10 items
Name	Field	Year	Lead author	Core idea	Why it hooked me	Best for	Length feel	Vibe	Nerdy flex
1Prospect Theory: An Analysis of Decision under Risk	Behavioral economics / psychology	1979	Daniel Kahneman	People value gains and losses asymmetrically and hate losing more than they like winning, breaking classic expected utility theory.	Reads like someone finally quantified every bad sports bet and publishing gut-call I’ve ever seen.	Reframing how you think about risk, pricing, and why people cling to losing strategies.	Long but modular—can graze the key sections without swallowing the whole thing at once.	Calm, devastating, politely overturning the table on “rational actor” models.	Casually drop “loss aversion” and “value function concavity” into a meeting and watch eyes widen.
2Judgment under Uncertainty: Heuristics and Biases	Cognitive psychology	1974	Amos Tversky	We use mental shortcuts—like representativeness and availability—that systematically warp our judgments under uncertainty.	Feels like someone ran controlled experiments on every hot take in a group chat.	Catching yourself (and other people) making very confident, very wrong predictions.	Dense classic article, but the examples keep it surprisingly readable.	Dry wit disguised as lab data; quietly roasting human intuition.	“This is pure availability bias” is my version of small talk at work.
3Belief in the Law of Small Numbers	Cognitive psychology / statistics	1971	Amos Tversky	People expect small samples to look like perfect miniatures of the population and wildly overinterpret streaks and blips.	Explains every overreaction to a tiny dataset, from baseball slumps to early sales numbers.	Anyone who has ever panicked over a week of metrics or a five-game losing streak.	Shortish, sharp, and to the point—like a very stern memo to your inner analyst.	Gentle at first, then ruthlessly unsympathetic to your intuition about randomness.	Perfect citation when you tell people to wait for more data before changing everything.
4A Mathematical Theory of Communication	Information theory	1948	Claude Shannon	Defines information, entropy, and channel capacity, giving us the math for how messages survive noise.	Feels like reading the source code for half of modern life, from compression to your group text.	Anyone who likes clean definitions, pretty equations, and surprisingly elegant prose.	Long, but skimmable if you focus on the definitions, figures, and section summaries.	Old-school Bell Labs: rigorous, understated, weirdly poetic in its precision.	Quoting entropy formulas when people say “information overload” is my party trick.
5The Strength of Weak Ties	Sociology / networks	1973	Mark Granovetter	Your loose, casual connections often matter more than close friends for spreading information and opportunity.	Explains half of New York career lore and why that one random coffee chat changed everything.	Rethinking networking, hiring, and how ideas actually move through a city or an industry.	Medium, with enough narrative to feel human, not just graph theory.	Quietly radical: takes everyday social life and turns it into a simple, powerful model.	Calling someone a “high‑betweenness weak tie” is my favorite niche compliment.
6The Magical Number Seven, Plus or Minus Two	Cognitive psychology	1956	George A. Miller	Human short‑term memory has a limited capacity—roughly seven meaningful chunks of information at once.	It’s the rare famous finding that actually changes how you design slides, forms, and checklists.	Editing anything cluttered—UI menus, onboarding docs, even your to‑do list.	Surprisingly readable essay with plenty of examples and jokes.	Cheeky, conversational, and self-aware about its own popularity.	Quoting Miller to justify cutting a bloated feature list never gets old.
7The Agenda-Setting Function of Mass Media	Media studies / political communication	1972	Maxwell McCombs	Media may not tell you what to think, but it powerfully shapes what you think about.	Makes nightly news lineups and homepage carousels feel like deliberate architectural choices, not coincidence.	People who love dissecting headlines, homepages, and which stories mysteriously vanish.	Medium, empirical, with clear tables and an easy-to-follow argument.	1970s empirical politeness hiding a very sharp critique of power.	Dropping “agenda‑setting effects” in a content meeting is my version of a record scratch.
8The Role of Deliberate Practice in the Acquisition of Expert Performance	Cognitive psychology / expertise	1993	K. Anders Ericsson	Expert performance comes from long-term, structured, feedback‑heavy practice—not just talent or generic experience.	Reads like a scouting report for skill: reps, feedback loops, and boring drills as secret weapons.	Anyone trying to get seriously good at anything—from jazz to code reviews.	Long review article; best read in strategic chunks.	Relentless, methodical, a little intimidating in its insistence on hard work.	Quoting practice‑hour distributions when someone blames “talent” is deeply satisfying.
9Computing Machinery and Intelligence	Philosophy of mind / computer science	1950	Alan Turing	Poses “Can machines think?” and proposes the imitation game (now the Turing Test) as a way to talk about it usefully.	Feels like listening to someone invent a whole conversation we’re still having in tech press releases.	People who like their AI debates with actual arguments instead of vibes.	Medium-length essay; surprisingly approachable given the topic and age.	Polite British provocation with occasional dry humor tucked in the footnotes.	You can say you’ve actually read the thing everyone name‑drops on LinkedIn.
10Portfolio Selection	Finance / economics	1952	Harry Markowitz	Shows how to build an “efficient” portfolio by balancing expected return against variance (risk).	Takes the gut feeling of “don’t put all your eggs in one basket” and turns it into clean geometry.	Anyone who secretly loves both spreadsheets and the idea of sleeping better at night.	Mathy but compact; the figures do a lot of storytelling.	Early‑50s quant energy: restrained, formal, sneakily revolutionary.	Explaining the efficient frontier on a napkin is my idea of small talk.

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