'Conversion', in Word you up: winning stories and poems from the 2014 Boroondara Literary Awards (Melbourne: City of Boroondara, 2014), 143-145.
Bibliographic record
Abstract
The 2014 Boroondara Literary Awards, marking the centenary of the start of World War 1, allowed for entries with the theme of Courage in Adversity, commemorating Australia’s involvement in the First World War. There was a further note to the effect that this could mean less conventional forms of courage, on the home front as well as overseas. My story ‘Conversion’ responded to this idea. 'Conversion' is a story about life-long learning. An old man goes to church – for a concert. He doesn’t want to go, but his daughter has asked him come with her, and he knows she’ll be disappointed if he doesn’t. What he experiences is something like a conversion. He’s prompted to reconsider some of his long-held assumptions about life and his relationships with his own long-dead parents. Maybe he’ll even come to know himself a little better. This was the winning story in the ‘Courage In Adversity’: Open Short Story section.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".