Bibliographic record
Abstract
This study is aimed to describe myths which appear in Edgar Allan Poe‘s ―The Raven‖ and to figure out the way that is used by Edgar Allan Poe to show the myths in the poem and convey the meaning of the poem itself. Archetype theory from Canadian critic Northrop Frye is used in this study in order to analyze the myths in ―The Raven‖ poem. Furthermore, to clarify the myths in the poem itself, this study uses a qualitative research as a method to collect, select, code, and analyze the data. In the research finding ―The Raven‖ poem by Edgar Allan Poe contains three types of archetype imagery, they are apocalyptic, demonic, and analogical imagery (analogy of innocence and analogy of experience). This poem also contains the four types of cyclical symbolism of archetype, they are divine world, human world, animal world, and mineral world. It is also found that this poem has a structure of sparagmos due to the dark myth and the confusion world that cover the theme of poem. Finally, this poem is divided into six phases of winter which is related to the literary genre of irony and satire that explain more about the sorrowfulness of the author, Edgar Allan Poe because his lover, Lenore leaves him.
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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 | 0.003 | 0.004 |
| 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 | 0.026 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".