Bibliographic record
Abstract
With its 2016 budget, the Government of Alberta laid out the basic details of the carbon tax rebate. The rebate is constructed to increase based on household size, and will decrease with income after a pre-set cutoff. The government has stated six in 10 households will be eligible for a full rebate, with an additional six per cent receiving a partial rebate. This paper examines the income distribution of Albertans, to determine how the rebate and income cutoffs affect different types of Alberta families. Using easily available data from Statistics Canada, we shed light on the question of who will receive a carbon-tax rebate. Based on 2013 data on median incomes, single-parent families, elderly families and single Albertans are all groups where a majority of households will receive rebates. In some cases, it appears well over 50 per cent of those groups will receive a full rebate. However, fewer than 50 per cent of Alberta families that are couples (with and without children) will receive a rebate. Still, even those that get a rebate will not necessarily exactly break even against the additional costs they incur from a carbon tax. Interestingly, the lowest-income households, which are most likely to qualify for a rebate, appear to be in a position where they will receive a larger refund than they will pay in carbon taxes. For households where incomes fall in the middle of the provincial distribution, the data suggest that the rebate will come close to compensating for additional costs of the carbon tax, although it may fall slightly short. The analysis presented below is a first pass at a very important question facing Albertans. When data from the 2016 census becomes available, we will be much better able to evaluate which Albertans will be eligible for the rebate. The census will enable a more precise evaluation of whether the rebate matches the government’s 66 per cent goal.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".