Meta-Analysis
Combining results from multiple studies to find robust conclusions.
"One study is a story. Many studies are evidence."
What is Meta-Analysis? Combining results from multiple studies to find robust conclusions. Aggregate lessons across projects rather than relying on one anecdote.
A meta-analysis of clinical trials reveals a drug's true effect.
Aggregate lessons across projects rather than relying on one anecdote.
Synthesize findings across teams and time periods.
Use the model. Pick the move.
Combining results from multiple studies to find robust conclusions. You've just seen this: A meta-analysis of clinical trials reveals a drug's true effect. Which lever does the model recommend?
Pick a lever. There are no neutral ones — every incentive funds a behavior somewhere.
Pick a reaction to Meta-Analysis
One tap. We'll point you at the most useful next surface based on how this hits.
The full taxonomy entry
Every concept in the Atlas uses the same structure — so Meta-Analysis can be compared, recombined, and cited like an element on a periodic table.
- Business
- Leadership
- Government
- Healthcare
- Education
- Sales
- Marketing
- AI
- Negotiation
- Media
- Public Policy
- Relationships
- Where in our org would Meta-Analysis most often show up unnoticed?
- Which metric, ritual, or contract clause quietly rewards Meta-Analysis?
- If we removed every payoff for Meta-Analysis, what behavior would replace it?
- Who benefits when Meta-Analysis persists — and who pays the cost?
- People defend the status quo using the language of meta-analysis.
- Decisions cluster around the easiest narrative rather than the strongest evidence.
- New data changes the slide deck but not the decision.
- Anyone naming the pattern is treated as the problem.
Every Atlas entry is a node in a knowledge graph. See the related rail below to follow the connections.
See Meta-Analysis through 3 lenses
Each layer of the Incentives OS reframes this concept with its own thinkers, vocabulary, and diagnostic question.
Do you actually know Meta-Analysis?
Three quick questions. Result is saved into your review streak — come back when the term is due to lock it in.
Which best describes Meta-Analysis?
Worked example, counter-example & concept map
On-demand AI analysis grounded in the Lab's research. Cached on your device after first run.
When you encounter Meta-Analysis, your prefrontal cortex has to do extra work to override the automatic response — and that override budget is finite.
Executive control, planning, impulse override, working memory, System 2. First thing to go offline under stress, fatigue, or low blood sugar. Why your 4pm decisions are worse than your 9am ones.
See Prefrontal in the Brain Atlas →Picked for you, from the Atlas
Ranked by shared learning paths, overlapping chips, and what you've saved.
Your capacity to learn, unlearn, and relearn faster than the environment changes.
Malcolm Knowles's principles of adult learning: self-direction, experience as resource, readiness, problem-centered orientation, intrinsic motivation.
Amishi Jha's research: attention is a finite, depletable, but trainable cognitive resource — short daily mindfulness measurably improves it.
Approach a situation as if you knew nothing.
Unusual or bizarre material is more memorable than common material.
Hierarchy of cognitive learning: Remember → Understand → Apply → Analyze → Evaluate → Create. Benjamin Bloom, 1956 (revised 2001).
Send the card, not just the link
A pre-rendered social card with the title, eyebrow, and URL. Copy the link, post it anywhere, or download the SVG for slides.
More definitions to follow
Every term in the Atlas connects to a dozen others. Pick any of these and see where it takes you.
Moving between abstraction levels — chunking up finds shared values, chunking down finds specifics.
We recognize faces from our own race more accurately than others.
Emotional states distort cognition and decision-making.
Believing abilities are static and cannot be developed.
We process evidence in ways that protect our group identity.
Greedy improvement loops climb hills that aren't the highest hill.
Underestimating the probability of bad outcomes — especially to us.
A behavioral relaxation of Nash: players choose better strategies more often, but not always — errors are smooth, not binary.
Institutions will try to preserve the problem to which they are the solution.
A controlled scenario, often impossible, used to isolate a variable and test an intuition or theory.
Tenure-track jobs replaced by low-paid adjuncts, lowering cost and quality.
Favoring suggestions from automated systems over conflicting human judgment.