Points Further North: An Acoustemological Cartography of Non-Place
Bibliographic record
Abstract
Abstract. This paper discusses the Points Further North project, a VR documentary that was undertaken with a view to foregrounding how sound can be deployed as the primary mechanism for laying out the complex, often subjugated relationships manifested between physical spaces and those who inhabit them. Specifically, It examines how ambisonic and haptic audio’s profoundly affective emotional, tactile and topologically enveloping capacities can be articulated within an acoustemological framework (acoustemology is best defined by ethnographer Steven Feld as “sonic ways of being in and knowing the world”) in order to evoke a heightened sense of awareness, perhaps even an agency, with respect to the largely abstracted ramifications arising from the consumerist lifestyles that are endemic to the developed world. The project exploits the possibilities inherent in the amplification of the vibratory and electromagnetic spectra that permeate our urban environments: infrasonic/tactile elements are disseminated via the Subpac wearable haptic interface in order to constitute a corporeal and emotional presence, and the radiant (yet invisible) transmissions of our information, economic and surveillance networks are captured and sonified via the via use of electromagnetic transducers. Both sonically and thematically, Points Further North seeks to uncover that which sound studies scholar Salomé Voegelin, terms “our locality on the invisible index of sound”, capitalizing upon sound’s capacity to delineate the ethereal topographies engendered via the vast, sublime – yet sublimated – infrastructures that we find ourselves immersed within.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".