The Struggle for Confiscation: An Imperialistic Look at Alfred Lord Tennyson’s Poem “Ulysses”
Bibliographic record
Abstract
The power of imperialism ascended during the Victorian age, when both the sense of nationalism and industrial revolution concurrently took place. Imperialism in its kind is the sense of domination of one group of people over another, or to a great point, it’s the domination of one country to other countries to confiscate its properties and belongings. Here in the poem written by Alfred Lord Tennyson, the poet tries to ironize the situation by showing and focusing on such an old king (may be the king of England), who has recently come back home from his travels and has complained about his “idleness.” This “idleness” for the king is equal to ceasing the kind of power, namely, if he does not move and battle, he has nothing for his country, and even he does not record a name for himself in the history of England. Thus the aim of the present paper is not only limitedto the relation between power and the sense of imperialism, a relation that leads to malicious and destructive behavior but it also condemns that kind of relation. However, it is done implicitly, as once the poet did in his poem, by showing the negative use of power in hands of some, like the king of England, who has done his best even at his death’s door to continue again and conquer wherever he sees that brings benefits to him. Not surprisingly; the poem also implies to the battle of Troy in the sense of imperial actions.
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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 | 0.002 | 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 | 0.012 | 0.025 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".