Bibliographic record
Abstract
The views expressed herein are solely those of the author and do not necessarily refl ect those of the Royal Commission on Renewing and Strengthening Our Place in Canada. Demographic Trends and Implications for Public Policy The population of Newfoundland and Labrador is declining due to falling birth rates and persistent outward migration. The population that remains is ageing and becoming more urbanised. This report examines the co-evolution of settlement, settlement policy and economic development initiatives in Newfoundland and Labrador. It is argued that out-migration is not unique to rural Newfoundland and Labrador, and that rural economic development initiatives are unlikely to result in substantial population gains in outlying areas. Moreover, there is no compelling argument that increases in rural population are desirable for their own sake, or as a way to improve overall economic effi ciency. The motivation for a policy response to demographic change is based on the entitlement of all citizens to reasonable levels of public services, even those residing in small, rural communities. If no attempt is made to alter the delivery of public programmes, it will become increasingly
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.904 | 0.845 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".