Coaching practices for George Bailey Effect
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For George Bailey Effect, these are the strongest matches in the current practice library.
Does this sound like the set of challenges you might be facing?
- I had one unusually bad stretch, then I changed something, and now things are better
- One thing happened that fits what I suspected and now I’m treating it as settled
- I’d settled on A over B, and then a third option showed up and somehow flipped me back to B
- Something blew up far bigger than it should have
- I get through the hard situations, but only with my little crutches
Practices that may help
- Expect regression to the mean in extreme outcomes
Unusually good or bad performance tends to be followed by more average performance — not because of what you did.
Base-Rate Neglect: Why We Ignore the Odds - The Ben Franklin Effect, Made Practical
When someone does you a favor, they unconsciously justify the behavior by deciding they must like you — otherwise why would they have helped? This cognitive dissonance reduction is called the Ben Franklin Effect, named after Franklin’s own documented strategy of borrowing a rare book from a rival legislator. The core mechanism has experimental support, though effect sizes and boundary conditions are worth understanding. - Update beliefs by degrees, not wholesale
Treat new information as evidence that shifts probabilities, not as proof that changes everything.
Base-Rate Neglect: Why We Ignore the Odds - Check whether a third option is changing your view of the original two
If a new option makes you change your preference between existing options, ask whether the new option should have that power.
The Decoy Effect — How an Irrelevant Option Changes Your Choice - Watch for lollapalooza effects — multiple models pointing the same direction
When several biases or forces combine on a single outcome, expect an extreme result.
Mental Models: Charlie Munger’s Latticework Approach - Dropping Safety Behaviors Within Experiments
Remove the subtle avoidance strategies (safety behaviors) that prevent experiments from genuinely testing the belief.
Behavioral Experiments: Testing Beliefs in the Real World - Base-Rate Neglect: Why We Ignore the Odds
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information. - Actively update your estimate of how much others notice
When you assume everyone saw your blunder, consciously cut the estimate in half.
The Spotlight Effect: Why You Think Everyone Is Watching - Run a disconfirmation experiment without the safety behavior
Enter the feared situation without the safety behavior and observe what actually happens.
Safety Behavior Fading, Made Practical - For many decisions, going with your gut outperforms lengthy analysis
Over-explaining reasons for a preference can actually detgrade the quality of affective predictions.
Affect Forecasting: Why You Mispredicted How You’d Feel
Related concerns
- Base Rate Neglect
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
- Base Rate Neglect Fix
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
- Base Rate Neglect Why We Ignore The Odds After A Loss
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
- Base Rate Neglect Why We Ignore The Odds As A Parent
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
- Base Rate Neglect Why We Ignore The Odds At Work
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
- Base Rate Neglect Why We Ignore The Odds During A Big Change
Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
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