Bibliographic record
Abstract
There are over 1, 000 First Nations and Inuit communities in Canada. Only 357 of these communities are consistently included in the most comprehensive public data source on economic activity, the Community Well-Being (CWB) Database. We propose using nighttime light density measured by satellites as an alternative indicator of well-being. We show that nighttime light density is an effective proxy for per capita income in the Canadian context and provide evidence that existing publicly available databases on well-being consist of heavily selected samples that systematically exclude many of the least developed communities. We show that sample selection into the publicly available data can lead to incorrect conclusions based on three applications: (i) the comparison of well-being across community types over time; (ii) an analysis of the historical and geographic determinants of economic activity in Indigenous communities; and (iii) a study of the effects of mining intensity close to Indigenous communities. Based on these applications, we suggest that using nighttime light density overcomes the biased selection of communities into the publicly available samples and, thus, may present a more complete picture of economic activity in Canada for Indigenous peoples. JEL Classification: I15, J15, J24
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".