A New Open Model Approach to Projecting Aboriginal Populations
Bibliographic record
Abstract
Changes in the size, composition, and geographic distribution of populations can have a substantial impact on the demand for a wide range of goods and services. Ways of understanding and projecting demographic changes among Canada’s Aboriginal populations are critical to the development of sound social and economic policies, as well as to the design, financing, and delivery of many programs and services to Aboriginal populations and communities. Population projections not only provide critical inputs to budgeting and to policy and program development, but may also provide important information for negotiations concerning Aboriginal self-government, land claims, and treaty entitlements. Methods used to project numbers for Canada’s Aboriginal populations have evolved considerably over the course of the past 30 years. This evolution has resulted, in large part, from the recognition that factors other than the traditional demographic components of fertility, mortality, and migration also play significant (and, in some contexts, the most important) roles in shaping Aboriginal population growth and change. These other factors, which include legislation, parenting patterns, the transfer of legal entitlement and/or Aboriginal identity from one generation to the next, and ethnic mobility, present considerable challenges to the development of Aboriginal population projections. This paper discusses the nature of these factors and their implications for the development of Aboriginal population projections. This paper is structured into four sections. Section 2 provides a brief discussion of the traditional or “closed” population projection model, its implied assumptions, and its limitations within the context of projecting Aboriginal populations. Section 3 identifies the structure and components of an alternative projection model, which incorporates the main features of an “open” population and illustrates how this type of model has be applied within the context of projecting the Registered Indian population. Section 4 extends the discussion to include additional issues and challenges which arise within the context of projecting other Aboriginal population groups. A final section looks at some of the existing gaps in demographic research, which need to be addressed in order to advance the development of more appropriate Aboriginal population projection methodologies.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".