Bibliographic record
Abstract
By evaluating the audience’s reaction to and involvement with feminism themes offered in both page poetry and spoken word poetry, the author attempts to determine which is best suited to reflect on these concerns, and what makes one a better communicative medium than the other. Both poetics and hermeneutics theories will be utilized to trace these variations in order to conduct an in-depth investigation of the work’s structures, form, and aesthetic qualities that would have particular impacts on the reader. The theories used will also allow the author to analyze the works under study’s verbal and nonverbal signals. Maya Angelou, Audre Lorde, and Jackie Hill Perry are the poets chosen for this research. They were chosen primarily for their reputation as feminists and civil rights activists, as well as for their fame in the realm of poetry. The three were well-known poets, yet their material took on distinct forms. The study reveals that, while page poetry excels in language, musical features, and more in-depth and original images, it does not thrive in public-opinion issues. When it comes to audience recognition and interaction, spoken word poetry is the most intimate and effective at generating a response, especially when it comes to women's issues. The paper's ultimate purpose is to have addressed a research gap in appraising spoken word poetry in this specific subject of critical themes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".