Bibliographic record
Abstract
Development of Canada's oil sands resource involves large scale, high-value, and long-lived assets, complex technology and infrastructure, large numbers of highly skilled people, and numerous environmental implications. Because of these components, there is potential for large consequences in the event that something goes wrong. However, because of these risks, Canada's federal government, provincial governments, and oil industry proponents have worked together to develop vast improvements to industry standards and regulation over the past several decades. Some of these regulatory improvements have meant an increase in corporate social responsibility, comprehensive and ongoing stakeholder consultation, and extensive research and technology improvements aimed at reducing the environmental footprint. Large companies such as Suncor, Syncrude and Cenovus have all implemented environmental and consultation programs to their corporate mandate in order to maintain the safety, sustainability and well being of environmental and Aboriginal communities, cultures and lands. For example, Syncrude regularly conducts tours of reclamation areas for representatives from local Aboriginal communities to ensure their efforts meet the standards of these stakeholders. Suncor, through its Suncor Energy Foundation (SEF), invests in Aboriginal education, training, and leadership development in order to help maintain Aboriginal community and culture. Additionally, Cenovus has implemented advanced technology such as remote cameras to monitor how wildlife interacts with above-ground pipelines, in order to better understand and reduced disturbance for wildlife habits. Despite such efforts and improvements, public opposition to the oil sands seems to be intensifying. Canada's oil sands resource has been subject to increased public scrutiny and criticism over the past several years and has been harshly stigmatized as 'dirty oil'. This stigmatization could be the result of factually incorrect and misleading information being reproduced through a 'social amplification of risk' framework, in efforts to further a particular political position or ideology of opposition. When misinformation and non factual risk statements are reproduced in many different outlets, there can inevitably be a promotion of fear, which may ultimately prevent important regulatory decisions being made based on solid science based evidence. Thus, if misleading and factually incorrect information is disseminated to a large number of people, the potential for stigmatization is high. This has the potential to affect political decisions, social perception, and ultimately for the oil sands, a license to operate. The problem of misinformation can generally impair efficient, economic and orderly development in the public interest. For the oil sands industry, misleading and factually incorrect information has been effectively disseminated to the public by environmental organizations, activists, and celebrities. One particular often heard example in media is a comparison of the footprint of the mineable oil sands to the state of Florida or New York. The Natural Resources Defense Council has claimed that "an area the size of Florida will become a wasteland if tar sands growth goes unchecked." However, this is a case of non factual and misleading information. Mineable oil sands will disturb an area maximum of 4800 square kilometers. Furthermore, this area will not be disturbed all at one time due to progressive reclamation. In actuality, the size of the disturbed area on the oil sands is about 0.3% of the state of Florida. Another example of misleading and non factual information is the claim that no oil sands area has been reclaimed. In reality, over 10% has undergone or is undergoing active reclamation. The government vigorously regulates reclamation efforts and will issue huge fines and potentially shut down or suspend operation for companies that do not comply with regulation and industry standards. In many ways the facts surrounding oil sands development do not accord with the 'dirty oil' reputation. Thus, it is important to examine how the oil sands got this negative public perception, given the potential policy effects for oil sands development. This study will focus on one particular project associated with oil sands development that has disproportionately been affected by the oil sands stigmatization; TransCanada's Keystone XL crude pipeline project. In recent months public protest and opposition against Canada's alleged 'dirty oil' has been strong enough to force the US government into withholding approval of the multi-billion dollar proposal of TransCanada's Keystone XL crude oil pipeline project which would carry oil from Alberta's oil sands to the United States Gulf Coast. In light of the politically-induced withholding of approval for such a large-scale infrastructure project, it is worthwhile to examine exactly what appears be happening in our society to initiate such strong opposition to a project that would have profound economic benefits. Factually incorrect and misleading statements have led to fears and stigmatizations of Keystone XL, indicating that the project is a victim of the social phenomenon described by social and risk analysts as the "social amplification of risk." This is a concept whereby actual physical risk, which a technical expert may judge to be relatively benign, is amplified by a series of social interactions, which often involve misinformation, that work to generate intense public concern. In some cases, the risk amplification can be to a degree that even an entire industry could be stigmatized as undeservedly dangerous. The social amplification of risk concept can be broadly applied to the nature of misinformation regarding benefits or costs. For instance, people who are in opposition of an industry or project may downplay economic or social benefits to amplify the risks associated with proceeding with it. In this study I examine the stigmatization of Keystone XL in the context of the social amplification of risk concept in an attempt to explain how risk and misinformation amplification, when applied to oil sands development, could have serious policy consequences and costs. Through this examination, I argue that the risks associated with Keystone XL, and in turn with Alberta's oil sands resource, have been amplified through factually incorrect and misleading information. I illustrate how this risk amplification has resulted in costs, not only to TransCanada, but also to Canada and the United States in general. After establishing this, I consider the possible policy responses that could help the oil sands industry, and individual oil sands infrastructure proponents such as TransCanada, to counteract this harsh stigmatism and risk amplification. I begin with a description of the "social amplification of risk" concept.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".