Introduction: Creative Communities: Regional Inclusion & the Arts
Bibliographic record
Abstract
Approximately 86 per cent of Australians live in the large cities that cling to the coastal periphery of the arid continent (Australian Bureau of Statistics 2008). Each of these cities is assumed to act as the administrative and cultural hub of their respective stale and territory. This metropolitan focus is replicated in many countries throughout the Global North. Over 80 per cent or Canadians (Human Resources and Skills Development Canada [HRSDC] 2014) and Americans (United States Census Bureau 2010) live in major cities and conurbations; similar patterns underpin most or the modern nation-states of the Global North. Simultaneously, these highly urbanized societies continue to extol the rural lifestyle as central to the nation's moral and historical compass. Within Australia, cultural knowledge of the country's rural and regional areas remains axiomatic to citizens' sense of self and national community. This is reflected in the creative practice of those in the major metropolitan centres. While creative products connect audiences with global trends, urban populations retain an intense emotional affinity with those who live what are imagined to be wholesome lives in regional and rural settings. In this book, we challenge the metropolitan focus in much of the scholarship regarding regional arts, along with the assumption that creative practice in the regions is necessarily a pale reflection of the cities. Instead, we argue that patterns of creative practice in regional communities are sustainable and innovative in distinct ways. Rather than compare regional and metropolitan experiences, we foreground the non-metropolitan as central to a broader understanding or self and community. In this way, this books contributors use the Australian example to suggest ways to re-imagine how regionalism might be constituted in the Global North, and explore new ways in which the creative arts can strengthen and refashion inclusive communities.
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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 | 0.001 | 0.001 |
| 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 | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".