Stealing words and ideas like a bandit. In academia, that's the kiss of death.

Playing fair in the world of science: informed consent, respecting privacy, no data tampering. Basic decency, folks.

A permanent link to a paper or dataset. Like a library card that never expires, no matter where the content travels.

Research on how we do research. Because sometimes we gotta fix ourselves before we break everything else.

A big summary of what's out there on a topic, so you don't have to read a thousand articles solo.

Reports, white papers, conference stuff—basically research that didn't get the VIP journal treatment but might still hold golden nuggets.

No anonymity. Authors and reviewers know each other, which (in theory) promotes honesty. In practice? Drama.

Tools that track who's citing who. Think of them as giant rumor mills for the academic world.

Your "science street cred" number—how many of your papers have been cited multiple times. Boost it if you can.

Any personal or financial ties that might sway your findings. Money talks, but we want to know when it's doing all the talking.

Rules about who deserves to be listed as an author, and who's just riding the coattails. We see you, slackers.

Yanking a published paper off the record because it's flawed, faked, or basically a dumpster fire of errors.

Where you confess whether you'll share your precious data or stash it away forever. Transparency vs. tight grip.

Extra charts, tables, and data. Like DVD bonus scenes—interesting if you're obsessed, otherwise easy to ignore.

Online hangouts (like arXiv or bioRxiv) where you can drop your paper before peer review. Real-time science, for better or worse.

Making research free for everyone. No paywalls, no private clubs—just knowledge out in the wild.

You lock in your methods and analysis plan before doing the study. That way, nobody can accuse you of monkeying with the data later.

Pay-to-play journals that skip real peer review. They'll publish your grocery list if you cough up enough cash.

Shiny positive results get published; boring or negative ones get shoved under the rug. Skews the entire research pool.

Your default "there's nothing to see here" stance. You usually want to prove this sad statement wrong.

Figuring out how many test subjects you need to get legit results. Too few, and you're basically flipping a coin.

Not just whether something happened, but how big the impact was. Tiny blip vs. giant leap—makes a difference.

A range that basically says, "We're pretty sure the real value is in here… but don't pin us to an exact digit."

That special number (often under 0.05) telling you if your findings are real or just random noise. Slip above 0.05? Try again.

Even the data analysts don't know who got what. It's secrecy on steroids.

Blind: Participants have no clue if they're on the real or fake treatment. Double-Blind: Participants AND researchers are in the dark. Cuts down on bias (and guesswork).

You register your methods and analysis plan before collecting data. Stops you from moving the goalposts when nobody's looking.

Your study's blueprint. No fancy decorations—just the step-by-step plan for what you're about to do.

The ethical bouncer for human-subject research. If your study design smells fishy, they'll slam the door in your face.