Bibliographic record
Abstract
Energy Humanities Imre Szeman When asked to name the event or scholarly work that has shifted the ground of theoretico-critical studies, I expect that most people will cast their gaze backwards. I’d like instead to look ahead, and to think about what we’re doing now that might have paradigm-altering consequences in coming years for critical work in the humanities. Studies of energy are just now blossoming within the greenhouse of the still-developing field called “energy humanities.” I think a critical encounter with energy will reshape how and why we undertake critical analysis. It constitutes a missing element in our understanding of the development of culture and society, including the shape of literature and of literary studies. And energy also belongs to our political vocabulary. Alongside the energy richness of modernity has been a corresponding energy unevenness that underlies the socio-political divide between global North and South. As we enter an era no longer defined by easy access to energy, struggles over energy resources are likely to define politics in the twenty-first century; they need to be part of the century’s literary and cultural studies, too. [End Page 21] Imre Szeman Professor and Canada Research Chair in Cultural Studies English and Film Studies University of Alberta Copyright © 2015 Association of Canadian College and University Teachers
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.290 | 0.121 |
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".