Bibliographic record
Abstract
Adaptations that Disinter and Disobey Shakespeare William Shakespeare is a staple in every literary curriculum; his works are constantly being adapted into books, cinema, live theatre and even memes. All of these various lenses and mediums serve to resurrect and modernize Shakespeare. However, the repeated “disinterring” of Shakespear is not simply an attempt at fidelity or reverence, but rather purposeful disobedience. In attempting to re-envision what makes a good adaptation, my video parallels what Shakespearean adaptations are to the original plays. The video is a series of images that provide movement and visualization to accompany the voiceover; it adapts my thoughts to the visual medium, rather than solely lying on auditory delivery. Adaptation is a way of having fun with the familiar and subverting the viewer’s expectations. It is about making something new out of the old, which uniquely represents the creator. Each format has its advantages and disadvantages, and I use mine to show how adaptation is a form of creative and subjective self-expression. Modern technology is one way we can engage with his works; it gives us a broader understanding of the discourse surrounding it. In my video, I imagine the discourse surrounding Shakespeare like a seed that grows into a tree: it has its roots in the far past, but its branches reach today. Shakespeare is still relevant, and it is this constant and ever-growing discourse that brings together different perspectives, cultures and traditions. Ultimately, to re-envision his work is to make the canon and literary tradition vital, dynamic and meaningful. Works Cited Dragon_fang. “Isolated Flute.” CanStockPhoto, https://www.canstockphoto.com/isolated-flute-2521314.html. Accessed November 18, 2021. “Garden meadow ground natural.” Svgsilh, https://svgsilh.com/image/303857.html. Accessed November 18, 2021. “Gravestone Drawing.” ClipArt Best, http://www.clipartbest.com/clipart-pc5XaKrdi. Accessed November 18, 2021. “Laying down skeleton clipart.” Clipart Library. http://clipart-library.com/clipart/2029478.htm. Accessed November 18, 2021. Milkovasa. “Viola on a white background.” Shutterstock, https://www.shutterstock.com/image-photo/viola-on-white-background-musical-instrument-163205225. Accessed November 18, 2021. Nikand4. “Clarinet isolated over white background.” Dreamstime, https://www.dreamstime.com/photos-images/clarinet-isolated.html. Accessed November 18, 2021. Paradies, Mark. “Red apple core on a white background.” TapRoot. 12 September 2019. https://www.taproot.com/live-your-core-values-exercise-to-increase-your-success/red-apple-core-on-a-white-background/. Accessed November 18, 2021. Tatniz. “Saxophone isolated under the white background stock photo.” iStock. 10 June 2019, https://www.istockphoto.com/search/2/image?phrase=saxophone+trumpet+blowing+ska. Accessed November 18, 2021. “Tree Clip Art -Clip Art Black and White Tree.” NicePNG, https://www.nicepng.com/ourpic/u2e6e6y3a9i1u2w7_tree-clip-art-clip-art-black-and-white/. Accessed November 18, 2021. Walterbioltta. “Trumpet on a white background shooting sideways.” iStock, https://www.istockphoto.com/photos/trumpet-white-background-no-people. Accessed November 18, 2021.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".