The school as a microcosm of communities and their heritage and the need to encapsulate this in the writing of school histories.
Bibliographic record
Abstract
The writing of school histories is a neglected sub-discipline in the study of heritage. It is, however, imperative that this aspect of the broad tapestry of our local and national heritage is analysed and preserved. As a microcosm of the community which it serves, a school reflects and engages with the greater political, social and economic issues and dynamics at any particular stage in its development. Often relegated to a purely celebratory document marking a centenary, half or quarter century, the account could be purely anecdotal or touch only on those aspects of the school which have contributed to school traditions, neglecting the broader framework within which it functions and with which it engages. It is critical that this aspect of heritage is preserved by historians who take the effort to research and write about this tiny snippet of our national heritage.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.066 |
| Scholarly communication | 0.021 | 0.021 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".