Review: <i>Both Sides Now: Writing the Edges of the North American West</i>, by Sheila McManus
Bibliographic record
Abstract
Book Review| May 01 2023 Review: Both Sides Now: Writing the Edges of the North American West, by Sheila McManus Both Sides Now: Writing the Edges of the North American West. By Sheila McManus. (College Station, Texas A & M University Press, 2022. 224 pp.). Benjamin H. Johnson Benjamin H. Johnson Loyola University Chicago Search for other works by this author on: This Site PubMed Google Scholar Pacific Historical Review (2023) 92 (2): 306–308. https://doi.org/10.1525/phr.2023.92.2.306 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Benjamin H. Johnson; Review: Both Sides Now: Writing the Edges of the North American West, by Sheila McManus. Pacific Historical Review 1 May 2023; 92 (2): 306–308. doi: https://doi.org/10.1525/phr.2023.92.2.306 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentPacific Historical Review Search In this slender yet substantive volume, Sheila McManus offers a historiographic account of recent scholarship on the Mexico-U.S. and western Canada-U.S. borders. McManus achieves the difficult feat of writing an account that is historiographically oriented yet rooted in the actual histories of these places, accessible yet rigorous, and even-handed in its description of scholarship but also helpfully proscriptive. “Borderlands have long memories,” the author proclaims in the book’s evocative first sentence, “they remember and reveal the messy, uneven, contested history of the constructed nature of the national spaces” (p. 1). In an introduction that traces the history of studying the regions that became international borderlands in the nineteenth century, McManus urges historians to “craft inclusive comparative frameworks” by examining the ways borderlands “retain their unique characteristics” and by focusing on the methodology of such studies (p. 3). The five body chapters that follow are both thematic and roughly chronological, serving... You do not currently have access to this content.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.180 | 0.238 |
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".