The results of Q8 were:
| Approach | Count | % of 81 |
|---|---|---|
| Moderately structured, with some flexibility in progression | 30 | 37% |
| Very clearly structured, with defined milestones and criteria | 23 | 28% |
| Lightly structured, allowing organic / self-driven progression | 20 | 25% |
| No strong preference | 8 | 10% |
Now, in the Key Themes & Recommended Analysis, you say:
Keep the structure flexible, not prescriptive
62% prefer moderate or light structure. The model should avoid overly rigid criteria and allow contributors to demonstrate value through multiple, flexible pathways.
But, when you look at the underlying data, it would have been equally true to say:
65% prefer moderate or very clearly defined structure
…and to use that number to recommend more rigid structure. It’s not clear that an unbiased analysis would have interpreted the data to mean “push in the direction of lighter structure”.
So questions on this:
- Why was the “62% prefer moderate or light structure” conclusion selected rather than the “65% prefer moderate or very clearly defined structure”?
- To what extent was AI used in putting together this analysis and writing the Magazine article? If any, can an “Assisted-By” tag be added, in compliance with the Fedora AI-Assisted Contributions Policy?