Estimating the Regional Economic Impacts of First Nation Spending in Saskatchewan, Canada
Bibliographic record
Abstract
It has been suggested that provincial and national multipliers may provide incorrect estimates of the economic impacts when examining distinct communities. Using data collected from a comprehensive survey of household spending on two First Nations in Saskatchewan, Canada, we use Input-Output models to refine regional multipliers for these distinct populations. We also estimate the rate of economic leakage and the economic impacts of First Nation spending. Results indicate that economic leakage rates for First Nation economies is roughly 90 percent; meaning that 90 cents of every dollar spent by First Nations for goods and services occurs off-reserve. Using our new multipliers, we find that First Nation spending contributes over $741 million to Saskatchewan’s GDP, creates approximately 11,244 full-time jobs, and leads to an estimated increase of over $462 million in labor force income for the province. If policy makers intend to build on-reserve economies, strategies must be found to recapture off-reserve spending by providing comparable on-reserve goods and services. In the absence of on-reserve economic development, First Nation economic growth will likely remain stagnant with few wealth generating opportunities and lower standards of living for First Nation members.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".