Sheryllynne Heggerty, Ordinary People, Extraordinary Times: Living the British Empire in Jamaica, 1756 (Montreal & Kingston: McGill-Queen’s University Press, 2023)
Bibliographic record
Abstract
reviews / comptes rendus / 371departs from existing scholarship.For example, Gun Country makes a very important contribution to the history of gun marketing, a topic that has received surprising little attention, and McKevitt could have been explicit about how his work builds on existing literature, such as Pamela Haag's 2016 book The Gunning of America: Business and the Making of American Gun Culture (Basic Books).For critics of American gun culture, Gun Country is a depressing read.In his introduction, McKevitt suggests that gun control advocates in the late 1960s worried that a failure to act might allow so many firearms to flood into the United States that future governments would be unable to meaningfully address the problem of gun violence.He says these advocates concerns "proved prescient.""There was no turning back," he suggests.(17) However, in the epilogue of Gun Country, McKevitt teases a more hopeful future."Meaningful reform is possible," he offers, though "it will require confronting mythologies and material reality head on.""If the gun country of the postwar era could be made, it can be unmade.Other worlds are possible."(263) Given the preceding 262 pages of analysis, however, readers may find this hopeful ending unrealistic.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".