“Happily Ever After” for the Twenty-First Century? Sex, Love, and Human Identity in C. S. Lewis’ The Chronicles of Narnia
Bibliographic record
Abstract
For better and for worse, classic fairy tales have come under severe criticism as paradigms of sexist patriarchy in recent decades. Likewise, C. S. Lewis has been viewed as sexist, even misogynistic. While many fairy tale and Lewis fans might be tempted to dismiss all of these criticisms as nonsense, gender is one of the predominant discourses of our time, our questions and the varied answers are significant, and in this essay I consider how Lewis’ development of the fairy tale genre in The Chronicles of Narnia offers timeless, possibly even surprising, Christian wisdom. How does Lewis portray sex, love, and human identity in these children’s novels? How does he deal with the related “happily ever after” concept? Are his representations of fairy tale motifs in sync with the genre, or do his novels suggest a significant departure? When might Lewis even be in agreement with feminist critics of classic fairy tales? Which aspects of cultural heritage does he affirm and which does he reject? With the sixtieth anniversary of the 1956 publication of The Last Battle, we have another opportunity to reconsider these important questions for the twenty-first century.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".