The Fellowship of the Wiki? OR, A Readers Response to Hogendoorn’s “There and Back Again”
Bibliographic record
Abstract
Having spent countless hours in my youth reading and re-reading J. R. R. Tolkien lore, it was hard for me to miss Adrian Hogendoorn’s appropriation of the subtitle of Tolkien’s most accessible work. Tolkien published The Hobbit in 1937 with the subtitle There and Back Again as a children’s adventure novel, detailing the quest of Bilbo Baggins, his 13 dwarfish companions, and the wizard, Gandalf. The quest to reclaim the kingdom and treasure of the Lonely Mountain begins and ends in Bilbo’s sleepy, but respectable hobbit-hole, Bag End. Although Bilbo eventually returns home to Bag End, his journey there and back again has profoundly changed him, and in more ways than just making him inordinately wealthy. According to Tolkien lore, Bilbo recorded his adventures for posterity in The Red Book of Westmarch, which became Tolkien’s source for The Hobbit. Likewise, Hogendoorn’s Principles of Learning (PoL) wiki contributions illuminate episodes of his learning journey. He makes the connections between moments of learning in courses and specific wiki entries in his wikiography. I am slightly envious of his use of the wiki and the wikiography as a capstone project for his MEd studies. This “off-label use” of the wikiography seems to be a brilliant means of further entrenching the learning of his program of studies.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.012 | 0.020 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.041 | 0.018 |
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".