Book Review: Catherine Belsey. <em>Shakespeare and the Loss of Eden</em>. New Brunswick, NJ: Rutgers University Press, 1999.
Bibliographic record
Abstract
Catherine Belsey's fine book, Shakespeare and the Loss of Eden, takes aim at 'family values' both today and in Shakespeare's England.Belsey claims that the 'family values' debated today (in England) emerged in the sixteenth-century; however, she argues, those values were not celebrated in their emergence.Instead, what she sees as the new sixteenth-century focus on marriage and family led many people, Shakespeare among them, to question whether 'family values' might bring happiness.If, today, those values are promoted by the cultural right, in Shakespeare's England they were seen, correctly in Belsey's view, as precarious, dangerous, and perhaps misplaced.Belsey aims to 'historicize and thus denaturalize family values' (xiv).There is, she argues, 'a problem at the heart of family values themselves' (xiv).While many people in today's England see 'family values' as the solution for social ills, in the sixteenth century, those values created the ills they are now designed to solve.In the course of her compelling argument, Belsey reads many material texts apart from and along with some of Shakespeare's plays.Belsey looks at images of Adam and Eve and the Fall depicted on bedheads, marriage chests, bed valences, and dishes.Engravings, paintings, and grave monuments help her to support her overall argument about the early modern 'ambivalence' regarding marriage and family (54).The book's final chapter on Hamlet discusses embroidered pillow covers and other visual images of Cain and Abel.Her detailed readings of these various material objects offer the reader a visual sense of the changing cultural history her book describes.She calls her project 'a history of representation' (5), and the variety of representations in question adds power to her argument about emergent 'family values' and the questions that surrounded those emergent values.Belsey claims that '[r]epresentational priorities change as values change, and history at the level of the signifier records these shifts of value' (6).Her book is lavishly illustrated with those signifiers, offering her readers the chance to see the history of values as people lived with them over the sixteenth and seventeenth centuries.The book's introduction is a theoretical discussion of its own parameters.A bit disconcertingly, Belsey begins by describing a living history museum in
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.112 | 0.110 |
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".