Socio-Psychological Alienation in Nathaniel Hawthorne’s “Young Goodman Brown”
Bibliographic record
Abstract
This paper investigates socio-psychological alienation in Hawthorne’s story “Young Goodman Brown”. It focuses on Brown’s psychological motivations that lead him to leave his village, Salem, on a journey to be taken literally and allegorically along with the inner conflicts thereof. Eventually, the result is a short-lived schism in his psyche. In fact, what urges Brown to step farther into the dark wood is an insistence to discover the whole truth so as to put an end to any vacillation between threatening possibilities suggested by the devil about the Puritan society to which he belongs. Thus, Brown turns into a rejectionist of all the teachings of his Puritan culture. In the end not only does he liberate himself from these cultural shackles, but he also seems to rise above them. So, while he lives among his countrymen he is not one of them. Brown’s new psychological state never allows him to accept the evil nature and the hypocrisy of his ancestry. Moreover, the psychological confusion in Brown’s psyche reaches its peak in a state of depression that we notice at the end of the story, which eventually puts him among those who have come to be called the “dark” romantics of the period, along with Poe, Melville, and Dickinson.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.016 | 0.013 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| 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".