Bibliographic record
Abstract
I. Creativity is like a rash : Everyone is now in the creativity game. Creativity has become a mantra of our age endowed almost exclusively with positive virtues. Twenty British cities at the last count call themselves creative. From Creative Manchester to Bristol to Plymouth to Norwich and of course Creative London. And ditto Canada. Toronto with its Culture Plan for the Creative City; Vancouver and the Creative City Task Force; or London, Ontario's similar task force and Ottawa's plan to be a creative city. In the States there is Creative Cincinnati. Creative Tampa Bay and the welter of creative regions such as Creative New England. In Australia we find the Brisbane Creative City strategy, there is Creative Auckland. Partners for Livable Communities launched a Creative Cities Initiative in 2001 and Osaka set up a Graduate School for Creative Cities in 2003 and launched a Japanese Creative Cities Network in 2005. Even the somewhat lumbering UNESCO through its Global Alliance for Cultural Diversity launched its Creative Cities Network in 2004 anointing Edinburgh as the first for its literary creativity. ......
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.073 | 0.060 |
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".