Bibliographic record
Abstract
Shakespeare's Shadow: Reaching Beyond Psychological Limitations The legacy of William Shakespeare is both awesome and imposing. It is a daunting task to be vulnerable and creative in writing when the success of figures like Shakespeare hangs over you like a cloud; shrouding you in the shadows of the literary world. The "anxiety of influence" is a literary-critical concept that was introduced by Harold Bloom, and it encapsulates the struggle to overcome the legacy of figures like Shakespeare, which is a battle that many writers and creatives endure. I will perform an original musical and lyrical composition as an accompaniment to my presentation on The Anxiety of Influence. I wrote a song that embodies the feeling of living in Shakespeare’s shadow as a way to draw emphasis to the need to overcome the anxiety of influence. My lyrics are designed to draw pity and a sense of helplessness in the face of an iconic legend and his literary footprint. I envision a world where writers are free from this anxiety and can create without psychological limitations, which will help people reach beyond in their everyday lives as they shirk the boundaries of self-imposed and societal limitations. The Anxiety of Influence interferes with a writer's ability to be bold and aspirational, which negatively impacts both creatives and consumers alike. In order to elevate our way of life and the way we think, we need people to dare to push boundaries and limitations. There cannot be groundbreaking new artists if our society's creatives are too intimidated to try, which is why I believe that understanding and overcoming the anxiety of influence is imperative to our ability to engage with and explore the world around us. Works Cited Bloom, Harold. The Anxiety of Influence: A Theory of Poetry. Oxford University Press, 1997.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.018 | 0.026 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".