‘She has her ladies too’: Women and Scottish Periodical Culture in <i>Blackwood's</i> Early Years
Bibliographic record
Abstract
This essay looks at some of the women who were published in and reviewed by Blackwood's Magazine in its early years. While the important contributions of women to the Blackwood's of the Victorian period have always been recognised, the Romantic-era magazine is better remembered for a sometimes aggressively ‘masculine’ tone. Women appeared in Blackwood's from the beginning, however, even if only in small numbers. Focusing first on reviews of major women writers – including Madame de Staël and Mary Shelley – and then turning to Felicia Hemans and Anne Grant, both of whom had poems published in the first year of the magazine's run, the essay argues that comments on these women and their work can illuminate the ways in which Blackwood's positioned itself in the competitive world of the Scottish periodical press.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".