Through Roots and Routes: On the Road 's Portrayal of an Outsider's Journey into the Meaning of America
Bibliographic record
Abstract
Jack Kerouac believed that his French Canadian roots held the key to his knowledge, despite the fact that he became known as the "principal avatar" of a generation of American youth. In his bestselling autobiographical novel, On the Road , Kerouac splits his ethnic (French) and national (American) sides into two figures, Sal and Dean, to demonstrate the deficits and benefits of both parts of a hyphenated identity. Italian Sal sees himself as the eternal outsider, whereas Dean is America itself. Yet Sal uses his outsider qualities to connect with other outsiders whose "roots" are beyond the limits of nationhood. And Dean, despite the seemingly endless freedom of his "routes" across the country, is stuck in old tropes of Americanness that do not afford him new possibilities. Together, they create a vision of America that is full of its own grandeur, while refusing to be insular. Jack Kerouac était persuadé que ses racines canadiennes-françaises étaient à la base de ses connaissances, malgré le fait qu'il ait été reconnu comme le «principal avatar» d'une génération de jeunes Américains. Dans son roman autobiographique On the Road , un succès de librairie, Kerouac illustre son côté ethnique (français) et son côté national (américain) en deux personnages, Sal et Dean, afin de démontrer les avantages et les désavantages des deux parties d'origines différentes. L'Italien Sal se voit comme l'éternel étranger, tandis que Dean représente l'Amérique même. Malgré cela, Sal emploie sa marginalité pour établir des liens avec d'autres étrangers dont les «racines» vont au-delà de l'esprit national, et Dean, malgré l'apparente liberté sans fin de ses « routes » d'un bout à l'autre du pays, est figé dans les signes d'un système fermé d'américanité qui ne lui offre aucune nouvelle possibilité. Ensemble, ses personnages créent une vision d'une Amérique imbue de sa propre grandeur tout en refusant de demeurer discrète et isolée.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".