Bibliographic record
Abstract
Alberta, Saskatchewan, Newfoundland and Labrador have each enjoyed a “rags to riches” story. Each of these provinces entered Confederation as poor cousins relative to the rest of the country; Alberta and Saskatchewan in 1905 and Newfoundland and Labrador in 1949. Rather remarkably, almost exactly four decades after entering Confederation each province began to enjoy the strong economic growth resulting from the development of their natural resources; Alberta and Saskatchewan in the late 1940s with the discovery of large pools of oil and Newfoundland and Labrador in the early 1990s with the development of off-shore oil. The governments of these provinces have similarly enjoyed the benefits of large amounts of revenue realized from the sale of these natural resources. In 2013-14, resource revenues accounted for 21 per cent, 22 per cent and 32 per cent of provincial revenues in Alberta, Saskatchewan, Newfoundland and Labrador, respectively. Unfortunately, the benefit of receiving large amounts of resource revenue must be weighed against two costs. The first is that these revenues, having flowed into provincial coffers without the need to impose high tax rates on citizens, are easily spent. The second cost is that the prices of resources are determined in international markets and so a significant amount of the revenues of these provinces is largely unpredictable and often volatile. All three provinces have fallen prey to the temptation to allow a large fiscal gap to open between the costs of providing health care, education, social assistance and other areas of provincial responsibility and the taxes imposed on citizens to pay for these services. Doing so has put all three provinces at financial risk should resource prices fall. Using a newly constructed data set spanning the period 1970 to 2014, I review the history of how Alberta and Saskatchewan have dealt with commodity price shocks and what this has meant for provincial finances. With that history as background, I review the response of the government of Newfoundland and Labrador to the flood of revenue it has received over the past decade as a result of the development of off-shore oil fields. The evidence is clear that Newfoundland and Labrador has adopted the same high-risk budgeting strategy as Alberta and Saskatchewan; a strategy that has seen the province choose to fund health care, education and social assistance using revenues that are unreliable and unpredictable. As Newfoundland and Labrador prepares for the release of its budget for 2015-16, it must begin to deal with the effect on its revenues of a dramatic fall in oil prices, a historically large budget deficit and a threat to the financial viability of its health, education and social assistance programs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".