Bibliographic record
Abstract
For Christmas 1998 my parents followed a long tradition of giving me a book related to Welsh culture. That year it was The Land and the Sea, a collection of the works of Kyffin Williams, published to celebrate his eightieth year. I have admired his work from when I first saw a portrait painted by him, of a much loved headmaster a quarter of a century earlier. He is an artist who has a profound understanding of place, both in his landscape work and his formal and informal portraits of the people of his native land, the Brythonic Kingdom of Gwynedd which dominated what is now Wales from the fifth to the thirteenth centuries. The Romans knew it as Venedotia , or the land of Venus, and I had the privilege of growing up there, walking its hills and sailing its coast. To sit on the summit of Tryfan as the sun descends over the Glyder ridge and Y Garn, casting shadows on to the precipitous slopes of Pen yr Ole Wen is a profound experience, not just of the aesthetic beauty of the landscape, but of one’s place, one’s identity, one’s place of belonging. There is a welsh word, Cynefin , which means all of that and more and has no equivalent in the English language, where it is crudely translated as habitat or place. In his preface to Kyffin Williams’book, Nicholas Sinclair connects the word Cynefin to the interaction between human beings and their environment that is the essence of the author’s work. I took that word as the name for a model that is the basis of this chapter, created to understand the different types of system within which we operate: ordered, complex and chaotic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".