Bibliographic record
Abstract
The Precipice is the sweeping story of Lucy Cameron, a young woman who seems destined to live and die in small-town Ontario. Into this place of monotony and petty incidents, of spiteful gossip and rigid moralism, appears Stephen Lassiter. Stephen is a Princeton-educated engineer from a wealthy New York family and Lucy's antithesis. Despite the chasm of their differences, they fall in love, marry, and begin life together in New York during the distressing years of the Second World War. It is a life that will nearly break Lucy in heart and spirit, however, as her husband faces disillusionment in his job and boredom in the serenity of his home life. While Stephen looks for excitement and approval elsewhere, Lucy must fight to retain her poise and dignity in order to survive. With its sustained contrast between the crushing deadness of small-town life and the glittering artificiality of New York City, MacLennan's third novel revealed a new level of maturity when it first appeared in 1948. A classic now back in print, with an introduction by renowned scholar and MacLennan biographer Elspeth Cameron, this timeless story portrays characters with a realism and fascination that is as rare as it is effective.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.063 | 0.015 |
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".