
Women, Fire, and Dangerous Things: What Categories Reveal about the Mind
4.4 stars from 171 reviews
Last checked: Jun 29, 2026
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Price range: $1.99 – $25.99
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Fans of these authors will like this...
- Steven Pinker
- Daniel Kahneman
- Antonio Damasio
Fans of these books will like this...
- The Structure of Scientific Revolutions
- Thinking, Fast and Slow
- Metaphors We Live By
Perfect for you if...
- You're fascinated by cognitive science and want to understand the foundations of how humans actually think, not how philosophers assumed we think.
- You read linguistics or psychology and keep encountering Lakoff's ideas secondhand, now ready to go to the source.
- You enjoy intellectual arguments that challenge common sense and aren't afraid of dense scholarly work that genuinely delivers on its claims.
Maybe not for you if...
- You want a quick self-help book about decision-making or productivity. This is theoretical cognitive science, not practical advice.
- You prefer narrative-driven writing. Lakoff builds arguments through research examples and philosophical critique, not storytelling.
- You're looking for beginner-friendly popular science. The book assumes comfort with linguistics, philosophy, and technical cognitive science concepts.
About this book
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Price History
Kindle price over time. Green zones = periods when the book was free.
Currently on sale at $3.99 — 85% off peak. Price has dropped 17 times over the last 5 years. Goes on sale roughly every 74 days.
Sales Rank
Amazon sales rank: lower number = better selling book. #1 is the bestseller.
Currently around #68K in the Kindle store — a steady mid-list seller.
Rating & Reviews
Purple line = star rating over time. Blue area = total review count growth.
Currently 4.4★ from 171 reviews
Gaining approximately 1 new review per month. Rating has remained stable at 4.4 over the tracking period.
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Actual Predicted
This book is currently discounted at $3.99. It typically returns to around $25.99.
Prices shown in USD from Amazon US. We continuously pull new data to improve tracking. If dates look old, it usually means there has been no significant change since the last data point.
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