Notice bibliographique
Résumé
Introduction Development of Western Canadian heavy oil and bitumen production from the end of price controls in mid 1985 to today has been a roller coaster ride for oil companies and their employees. Activities in response to the current oil price drop suggest this trend is continuing. The results to the oil industry have been fragmented, including inefficient efforts to advance technology and a need for repeated reorganization. The results for many employees have been insecurity, career disruption and general frustration. While some may point out that this period of time has seen a great deal of technical development, I feel that much more could have been accomplished under more stable circumstances. It seems prudent that those of us in the heavy oil industry should periodically stop and ask ourselves why this cycling of activity occurs, and explore options for dampening the severity of the booms and busts. My main purpose in writing this article is to encourage candid dialogue. Data Collection When I was contemplating writing an article on this subject, I talked to a number of people working within the Calgary oil patch. Input was obtained from workers in industry, research, education and the government. Nearly everyone expressed strong opinions, but very few gave me the impression they wanted to be quoted or identified. From the perspective of the 'soft science' of human behaviour, this high interest in expressing opinions but low interest in public ownership of them is likely an important piece of data. Statistical data were not hard to locate, but most of these data were proprietary and unavailable for citation in this article. For example, some investment companies have detailed documents discussing current events in heavy oil and making predictions about its future. It is a little unnerving to read these sterile, economic prognoses of our chosen field of endeavour. One begins to wonder if the investment companies collectively have the ability to influence the economic state of the oil patch more than their workers do. There are also a number of commercial analytical studies on the booms and busts experienced in the Canadian heavy oil industry. I will not try to duplicate or improve upon them. My statistics will be limited to noting the scale of the booms and busts by citing that over 26,000 Canadian workers appear to have been laid off between 1985 and 1994(1). The fraction working in heavy oil was not stated, but it was likely a significant number. It would also be very difficult to determine the number of these people who subsequently found employment back in the heavy oil field. Regardless of these unknown factors, it is apparent that significant disruption to the industry occurs during the boom and bust cycles. Another important conclusion from the historic data is that all booms or busts will end within a few years. They should not be viewed as permanent. As one of my experienced and accomplished friends in heavy oil recently told me, "It is unfortunate that decisions are often made on the assumption that the "current" heavy oil price will go on forever."
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».