Bibliographic record
Abstract
This issue of the British Journal of Canadian Studies showcases a range of original research by emerging scholars writing about the literature of Canada. These scholars, drawn from the United Kingdom and elsewhere in Europe, represent the next generation of academics engaged in research, analysis and writing in the field of Canadian Studies.As with many projects, this issue began as a conversation between friends and colleagues - Christopher Kirkey, Director of the Center for the Study of Canada at State University of New York College at Plattsburgh, and Tony McCulloch, Senior Fellow in North American Studies at the UCL Institute of the Americas. Reflecting on the need to encourage younger scholars working on Canada, and building on a model already successfully employed by SUN Y Plattsburgh's CONNECT programme, the decision was taken in May 2013 to organise, promote and convene a colloquium at University College London in the summer of 2014. A call for papers was issued, aimed primarily at doctoral students and early-career professionals, and resulted in some thirty proposals. Twenty-one participants, from all over Europe and representing a variety of academic disciplines, subsequently presented their research at the 'Issues in Canadian Studies: New Voices on Canada' colloquium held at the UCL Institute of the Americas in Bloomsbur y, central London, between 10 and 12 July 2014.The colloquium featured, most prominently, a compelling focus on papers dedicated to Canadian literature. As editors - following formal presentations, extended discussions, and multiple academic peer reviews by several senior scholars - we chose to commit this issue of the BJCS to six essays grounded in the study of Canadian literature, broadly defined. We are also pleased to note that the authors of several other papers given at the colloquium have been encouraged to submit their work to the BJCS for consideration in future issues.In this special issue Sarah Galletly, from the UK but currently based in Australia, focuses on the highly popular Canadian author, Lucy Maud Montgomer y, and her often overlooked short fictional feature submissions to two prominent Canadian periodicals, Chatelaine and the Canadian Home Journal. Will Smith, also from the UK, examines two 'little-known popular novels', Hopkins Moorhouse's Every Man for Himself and Peter Donovan's Late Spring, and shows that these Toronto-based writers of the early twentieth century reflect and radiate the emergence of urban realist fiction in and about Canada. …
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".