The Sky is Falling - Again: Oil Price: Biggest Factor Affecting the Industry
Bibliographic record
Abstract
Forum The slumping oil price is the talk of the industry. From field hands and technical teams getting laid off to slowing down of projects until 2016 or later, the oil price is affecting many in the industry. The Way Ahead Forum section editors sat down with stakeholders from different sections of the industry to get a better picture of what the recent oil price changes mean to business. What would you define as “low” in oil prices? Euan Mearns (EM): This is a good question. The best answer I can suggest is that the price is low when it falls below the level where companies can make a profit. The corollary would be that the price is high when companies make large windfall profits. Since different companies and states have different operating costs and these operating costs vary with time, there is no unique definition. But I believe at USD 50/bbl few, if any, companies are making a profit, hence we may safely assume that USD 50/bbl is low. Jared Wynveen (JW): Generally speaking, I think a low oil price is one in which we can no longer sustain continued development and expansion of our resources. Depending on the play, low pricing might be anywhere from USD 40/bbl (WTI) to USD 80/bbl, but ultimately it all depends on the specifics of the operator, the reservoir, and the product quality. James Fann (JF): Energy prices have always historically moved in cycles. Instead of thinking of a low oil price as an absolute number, for Canadian energy producers, I would suggest a low oil price would be one such as to slow down and potentially stop the development of new projects or expansions that would increase the oil supply. This price would cause supply to either decrease or remain flat.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".