Alberta's $22-Billion Lost Opportunity: How Spending beyond Inflation + Population Growth Created Alberta's Red Ink
Bibliographic record
Abstract
Alberta’s $22-Billion Lost Opportunity calculates the economic cost of the province’s inability to hold government spending to the rate of inflation plus population growth. The report examines the history of Alberta budgets starting in fiscal year 2005/06 up until 2012/13 and concludes that successive Alberta governments failed to control spending and plan for fluctuating resource prices.A review of actual choices governments made shows a pattern of increased program spending well above the rate of inflation and population growth and as a result, a string of five consecutive deficits. The report calculates that after inflation and population growth are factored in, Alberta program spending rose to $10,526 per person in 2012/13 from $9,594 in 2005/06.In total, if Alberta’s governments had held program spending increases to the rate of inflation plus population growth since 2005, the province would have spent $22.1 billion less than it did. In the current year alone, program spending is $3.6 billion higher than it would have been if spending increases matched the rate of inflation plus population growth since 2005. Additionally, the province would have run a surplus budget in every budget year since, including during the 2008/09 recession.It concludes that if the Alberta government is serious about balancing its budget, then it should consider the following options: Provide annual estimates of public sector compensation costs in the broad public sector relative to provincial government expenditures; Review overall public sector compensation with an eye to bringing such compensation in line with the private sector; Freeze overall spending growth for a time to make up for past increases that far outran population and inflation growth in Alberta; and Commit to holding any future program spending increases to the rate of inflation plus population growth.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".