Innovation Policies in Alberta's Oil Sands
Bibliographic record
Abstract
Alberta’s oil sands are currently faced with economic and environmental challenges. The oil sands provide economic benefits both to Alberta and to the rest of Canada. However, environmental challenges and rising costs are putting the operation of the oil sands at risk. As this resource is publicly owned, coherent and focused public policies should be put in place to aid the further development of the oil sands. Through examining current oil sands trends, it becomes apparent that innovation is a promising solution to many of the challenges posed to the oil sands today. Increased productivity is mainly the result of innovation. Further, technological innovation has also provided the oil sands with improved environmental records and has provided increased economic efficiencies. Based on the literature available, there is a strong consensus from key players that innovation has a significant role in creating solutions for challenges in the oil sands. This paper describes governmental programs, and private institutions which promote and support innovation within the oil sands industry. As the oil sands and the significance of innovation, together, are relatively new, academic literature has not addressed this topic. My research indicates that, although there are efforts currently in place policies and programs to foster innovation in this industry, there is certainly room for expanding them. Also because of the lack of publically available evaluation and outcome reports for these policies and programs, it was difficult to determine the impact that each of these initiatives have had. As this paper was being written, advancements were already being made to the promotion of innovation within Alberta. Earlier this summer, the Alberta Innovation Council was established. It is meant to play a guiding role in Alberta’s innovation future and is expected to help create a healthy innovation ecosystem within Alberta. It is with optimism, that I believe this council will help facilitate additional innovation investment within the oil sands. The key recommendations stemming from my research include: increased focus on evaluation of all innovation policies and programs, continued collaboration amongst all key players in the oil sands industry, use regulation and legislation to increase innovation, and improved focus on ways to incentivize innovation. Lastly, increased financial support from the governments should be considered as a support mechanism.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| 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".