Alive inside, dead outside: Cultural implications of the documentary Alive Inside
Bibliographic record
Abstract
This article reflects on the cultural discourse of Alzheimer’s Disease (AD) that has rooted the disease in numerous metaphors preserving the unknown aspects of AD and supporting its status as a ‘social death’. Through engagement with Michael Rossato-Bennett’s documentary film, Alive Inside: A Story of Music and Memory, a number of scenes from the film are discussed. Through qualitative discourse analysis, we challenge the cultural discourse of AD highlighted throughout Alive Inside, and outline some cautions on the iPod project for persons with AD, in particular isolation caused by using headphones to engage with the music. While there are numerous benefits in music listening for persons across the lifespan; for an individual with AD it is important for a healthcare professional or caregiver to monitor the listening experience, and to consider sharing the music with them via speakers. This is a responsible and effective way of including music in the overall care plan for an individual with AD. Further, the benefits of music experiences can be more fully realized in many cases when they are implemented by a credentialed music therapist in working with vulnerable populations.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.036 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".