Energetic, a novel: An Exploration of Female Business Leadership in Alberta Energy
Bibliographic record
Abstract
This thesis argues that an evolved version of the literary genre, petrofiction, would improve how citizens of hydrocarbon-extracting communities understand the linkages between oil and life’s abstractions in the current decade and enhance energy literacy, more broadly. This, in turn, would promote more productive public conversation around transitioning to a low carbon future in Canada. A sample of five texts are close read in order to analyze petrofiction conventions over the past century. The primary conclusion of this analysis is that the women leaders of the present are not represented in petrofiction; consequently, the creative portion which resolves this void offers a model for an evolved petro-novel. Energetic is a novel about two Alberta characters over the course of four months. When the story begins, Barbara Warren and Antoinette “Tony” Nailer are strangers, each employed in different parts of the petroleum sector. A catastrophic event at an oil sands upgrader brings them together as antagonists. This story is set in the current moment of ecological and economic upheaval, in the initial phase of our transition from the world’s heavy dependency on oil in order to underscore the pace of technological progress, the impact of government policy, the role of the media, and the weight of personal and corporate decision-making today. It is inspired by history being written, in real-time, by the promises and actions of Albertans working in the sector. This novel subverts the limited and skewed record of this history as documented by polished corporate literature, inconsistent media coverage, and fleeting social platform posts. Energetic’s narrative unpacks the business tools available today and the current barriers or opportunities to act. Unlike the evil oilman trope common to petrofiction texts, the two female protagonists in this story engage with industry challenges while maintaining a personal distance from the threatening effects of oil extraction. Competition, ego, and greed do not form the motivational foundation of these two business leaders. This novel interrogates the economic and social conditions that shape responses to a demand for transition from the unique perspective of Albertans, a population residing in proximity to natural resource extraction activity, and a population seeking nuanced energy-literate conversations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.015 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".