Bibliographic record
Abstract
What can we learn about authorship through a reading of a writer’s archive? Collections of authors’ manuscripts and correspondence have traditionally been used in ways that further illuminate the published text. JoAnn McCaig sets out to show how archival materials can also provide fascinating insights into the business of culture, reveal the individuals, institutions, and ideologies that shape the author and her work, and describe the negotiations that occur between an author and the cultural marketplace. Using a feminist cultural studies approach, JoAnn McCaig “reads in” to the archives of acclaimed Canadian short story writer Alice Munro in order to explore precisely how the terms “Canadian,” “woman,” “short story,” and “writer” are constructed in her writing career. Munro’s correspondence with mentor Robert Weaver, agent Virginia Barber, publishers Doug Gibson and Ann Close, and writer John Metcalf tell a fascinating story of how one very determined and gifted writer made her way through the pitfalls of the culture business to achieve the enviable authority she now claims. McCaig’s discussion of her own difficulties with obtaining copyright permission for the book raises important questions about freedom of scholarly inquiry and about the unforeseen difficulties and limitations of archival research. Despite these difficulties, McCaig’s reading of the Munro archives succeeds in examining the business of culture, the construction of the aesthetic, and the impact of gender, genre, nationality, and class on authorship. While on one level telling the story of one author’s career — the progress of Alice Munro, so to speak — the book also illustrates how cultural studies analysis suggests ways of opening up the rich but underutilized literary resource of authorial archives to all researchers.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.344 | 0.187 |
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".