A Detailed Analysis of the Productivity Performance of Oil and Gas Extraction in Canada
Bibliographic record
Abstract
In recent years, the productivity performance of oil and gas extraction in Canada has been dismal. Based on official real GDP and labour input estimates from Statistics Canada, labour productivity in oil and gas extraction fell 8.23 per cent per year between the 2000 cyclical peak and 2007, with capital productivity down 5.97 per cent per year over the same period and total factor productivity (TFP) off 6.67 per cent per year between 2000 and 2006. Among the various hypotheses put forward to explain these trends, the most robust seems to be that higher output prices have suppressed productivity growth through two effects: increased exploitation of low-productivity marginal deposits, and business decisions based on profitability rather than productivity. Despite the rapid decline in productivity in oil and gas extraction, it is not necessarily true that Canadians are worse off. In fact, increased output prices and employment shares in the industry, as well as the high productivity level, have resulted in positive contributions to Canada‟s aggregate labour productivity growth from 2000 to 2006.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".