Measure for measure : quantification in The Colony of Unrequited Dreams
Bibliographic record
Abstract
This paper analyzes Wayne Johnston's novel The Colony of Unrequited Dreams in terms of the ways in which measurement, and mathematics more broadly, are incorporated into the autobiographical narratives within the text. The main character, the fiction fictionalized Joseph Smallwood who is based loosely on Newfoundland's first premier, often speaks of both numeric and nonnumeric measurements and calculations in his descriptions of instances of social and economic hierarchies, human frailty and intractable problems, both personal and political. As someone who intends greatness for himself and his country, Joe's life and career are followed as he attempts to both evaluate and remedy the social and economic conditions which have meant poverty and despair for his fellow Newfoundlanders, while at the same time fulfilling his personal dream of bringing the island colony into the Canadian Confederation – a dream he finally achieves in 1949. The use of mathematics to describe unfortunate, often tragic situations underscores the dominant theme of unrealized aspirations, both for the main protagonists in the story as well as for the people of mid-20th-century Newfoundland.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".