Bibliographic record
Abstract
The Cape Breton Regional Municipality (CBRM) is a beautiful region of approximately 2,400 square kilometres located on Cape Breton Island in the eastern part of Nova Scotia. As is the case with many economic regions in Atlantic Canada, Cape Breton Island has long been characterized by both an aging and declining population. For many decades, each year hundreds of young adults have migrated out of the region for educational and work opportunities in other areas of Nova Scotia and Canada. The result has been a consistent shift in the shape of the CBRM's age pyramid. There have been ever fewer young people, and far more people in the older age cohorts. In 2016, almost 23% of CBRM's total population was aged 65 or older. More broadly, during the 2006 to 2016 period, the share of people across all parts of Nova Scotia aged 65 years of age and older increased by 33%. It is likely that within another decade, approximately one-quarter of the provincial population will be at least 65 years of age. In terms of the geographical distribution of the population within the CBRM, approximately 72% of the total residents live within small urban and suburban communities with total populations below 30,000 people. Historically, a number of these communities were established around natural resource industries – namely fishing harbours or coal seams/mines. Sydney, founded in 1785, is the largest of the small urban centres and Sydney's principal industry for many decades was steelmaking. In total, these small urban communities account for approximately 4% of the entire land mass of the region. The other 28% of the population is widely scattered about the remaining 2,300 square kilometres. These rural residents have access to relatively little physical public infrastructure. Within this context, the CBRM is increasingly challenged to identify initiatives and programs that will effectively accommodate and support an aging population. CBRM is among the poorest municipalities in Nova Scotia, and in Canada for that matter (as measured by taxable assessment per capita). This reality has impacted the decisions that have been taken by both the CBRM's municipal council and by the administrative staff.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.449 | 0.104 |
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".