“Suit the Action to the Word, the Word to the Action”: An Unconventional Approach to Describing Shakespeare's <i>Hamlet</i>
Bibliographic record
Abstract
Without access to audio description, individuals who are visually impaired (that is, are blind or have low vision) may be at a unique social disadvantage because they are unable to participate fully in a culture that is based on and heavily saturated by the enjoyment of audiovisual entertainments (Packer & Kirchner, 1997). Audio description was introduced as an adaptive after-the-fact strategy to give individuals who are visually impaired better access to media (Fels, Udo, Ting, Diamond, & Diamond, 2006). With audio description, visually important elements of the entertainment experience are described during pauses in the dialogue (Packer & Kirchner, 1997). Conventional audio description practices, as outlined by Snyder (2005, 2007), have been adopted as an access strategy for live theater, television, and film, although little research has informed these practices (Gerber, 2007). Alternative audio description strategies are also being explored and developed, mainly by theater (for example, British Council for the Arts, 2007; Graeae Theatre Company, n.d.) or dance troupes (for example, CandoCo Dance Company, 2008; StopGap, 2008) whose mandates are focused on the inclusion of individuals with disabilities in their casts. We believe that audio description is a creative process, and from working firsthand on live audio description projects we learned how cognitively demanding live description is on a describer. We recognize that audio describers are generally volunteers and have a genuine interest in making the theater accessible to individuals with visual impairments. In this article, we present a summary of conventional and alternative audio description practices. We discuss a case account of an alternative audio description strategy that was prepared for a live production of Hamlet using the subjective, emotional style proposed by Fels, Udo, Diamond, and Diamond (2006) and Fels, Udo, Ting et al. (2006); and used by Udo and Fels (in press). CONVENTIONAL AUDIO DESCRIPTION Formal audio description is a relatively new media access technology compared with others, such as closed captioning. Audio description has existed for many years, however, as an ad hoc and access strategy in which friends and family members acted as informal describers, whispering descriptions to their friends and relatives who were visually impaired (Packer & Kirchner, 1997). In the 1970s, Gregory Frazier formalized audio description by defining formal procedures and processes for the description of media and cultural events (Snyder, 2005). In the 1990s, WGBH Radio & Television began offering a Descriptive Video Service as part of its broadcasts (WGBH Educational Foundation, n.d.). Numerous theater groups in the United States and the United Kingdom have also embraced these technologies and techniques for live theater. In 1981, Margaret Pfanstiehl and Cody Pfanstiehl were among the pioneers to develop audio description techniques for live theater. Additional guidelines for the creation of audio description for television, film, and live theater exist (Audetel Consortium, 2000; Audio Description International, 2005). However, most of these guidelines tend to rely heavily on anecdotal evidence and the historical use of a specific process, rather than one validated by published research. Pfanstiehl and Pfanstiehl (quoted in The Play's the Thing, 1985, p. 91) cautioned describers not [to] evaluate or interpret, but rather be like the faithful lens of a camera and encouraged them to describe visual elements without drawing assumptions for the listener. In doing so, the describer must interpret and translate important visual action or stimuli (costumes, setting, lighting, and so forth) as objectively as possible. Since limited time is available to describe visual stimuli, describers must use precise and highly descriptive language. There has been limited research on the effectiveness and impact of live audio description on audiences. …
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".