Bibliographic record
Abstract
This article explores and proposes a model of hearing based upon an emergent line of thought known as the ‘enactive’ or ‘embodied cognition’ approach. This approach views the various modes of perception (sight, hearing, etc.) as styles of relating rather than processes carried out in the brain. Put another way, these approaches envision experience as constituted by embodied, perceptual relationships to the world. According to the phenomenological perspective of Maurice Merleau-Ponty, every self is constituted by perceptual, embodied relations within a lifeworld. For Merleau-Ponty, and for scholars like Francisco Varela, Alva Noë and Shaun Gallagher, this is no metaphor. It is a material description of the ordinary and everyday relations that constitute our selves in the world. As Noë reports, breakthroughs in neuroanatomical and neuropsychological research methods have led to considerable excitement and energy being poured into cognitive studies. It is thought that by these means we might even be able to ‘see’ consciousness at work. Yet Noë is highly sceptical of this ambition because an ‘explanatory gap’ remains between the data (images of brain activity, etc.) and true understanding of perceptual experience. Working from this critique, Noë and Kevin O’Regan have argued convincingly for a sensory-motor account of vision and consciousness. Currently, there is virtually nothing written on the possibilities for an enactive model of hearing. Therefore, my goal in this article is to initiate a sketch of such a model. I contend that this alternative approach may prove to be very enlightening with respect to studies of film and television reception, which otherwise tend not to notice the meaning-making activities of the body.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.015 | 0.025 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| 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".