Bibliographic record
Abstract
"To me what is most important is to come to grips with both colonial history and contemporary life," writes Emma LaRocque in her essay, "When the 'Wild West' Is Me," on de-mythologizing the cowboys and Indians of popular culture. What makes this new collection fresh is its emphasis on connections between past and present communities in the Canadian West. Eighteen thought-provoking articles are organized in three parts: "Images of the West," "Challenging Western History and Frontier Myth-Making," and "New Frontiers." A scholarly introduction and editorial analyses between the various sections bind the articles to key themes of community building and an always-spinning web of human connection. This makes the significance of the collection greater than most of the articles would be alone. Authors from the disciplines of history, English, musicology, folklore, art history, architectural history, and sociology focus on fluidity in time and space. The editors perceptively note that "frontier" has suffered from "both vague and overly precise usage of the word" and explain that the concept informs this collection for practical reasons of "habit and history" and so old usages can be challenged. Some essays also touch on "metropolitanism" which the editors nudge usefully into a global framework.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".