Back to Progymnasmata

On Whether One Should Marry

A thesis examining the question of whether marriage is beneficial for human flourishing.

status: Notes

Status Indicator

The status indicator reflects the current state of the work: - Abandoned: Work that has been discontinued - Notes: Initial collections of thoughts and references - Draft: Early structured version with a central thesis - In Progress: Well-developed work actively being refined - Finished: Completed work with no planned major changes This helps readers understand the maturity and completeness of the content.

·
certainty: likely

Confidence Rating

The confidence tag expresses how well-supported the content is, or how likely its overall ideas are right. This uses a scale from "impossible" to "certain", based on the Kesselman List of Estimative Words: 1. "certain" 2. "highly likely" 3. "likely" 4. "possible" 5. "unlikely" 6. "highly unlikely" 7. "remote" 8. "impossible" Even ideas that seem unlikely may be worth exploring if their potential impact is significant enough.

·
importance: 6/10

Importance Rating

The importance rating distinguishes between trivial topics and those which might change your life. Using a scale from 0-10, content is ranked based on its potential impact on: - the reader - the intended audience - the world at large For example, topics about fundamental research or transformative technologies would rank 9-10, while personal reflections or minor experiments might rank 0-1.

Content goes here...

Sign in with GitHub to comment

Loading comments...
Citation
Yotam, Kris · Apr 2025

Yotam, Kris. (Apr 2025). On Whether One Should Marry. krisyotam.com. https://krisyotam.com/progymnasmata/thesis/on-whether-one-should-marry

@article{yotam2025on-whether-one-should-marry,
  title   = "On Whether One Should Marry",
  author  = "Yotam, Kris",
  journal = "krisyotam.com",
  year    = "2025",
  month   = "Apr",
  url     = "https://krisyotam.com/progymnasmata/thesis/on-whether-one-should-marry"
}
Quote of the moment
Looking back, it's clear we overcomplicated things. While embeddings fundamentally changed how we can represent and compare content, they didn't need an entirely new infrastructure category. What we label as "vector databases" are, in reality, search engines with vector capabilities. The market is already correcting this categorization—vector search providers rapidly add traditional search features while established search engines incorporate vector search capabilities. This category convergence isn't surprising: building a good retrieval engine has always been about combining multiple retrieval and ranking strategies. Vector search is just another powerful tool in that toolbox, not a category of its own.
Jo Kristian Bergum (https://twitter.com/jobergum/status/1872923872007217309)
Kris Yotam
Kris Yotam
long-form stable essays
Updated
2026-05-12
Reading time
~1s

in Naperville, IL
Last visitor from Mitaka, Japan