“Having Walked Alongside You”: A Conversational Exchange on Territory and Sound in Motion
Bibliographic record
Abstract
As two artist-scholars engaged in research-creation, our goal with this project was to enact a performance/discussion regarding settler-colonialism, sound, performance, and our relationships to land, body and time. During the initial “lockdown phase” of the COVID-19 pandemic in March 2020, we carried out a mediated conversation via WhatsApp voice memos, hiking towards each other along and across the Oldman River, then retracing the other’s path back to our respective points of origin. This collaborative project aims to decolonize the academic paper through a process which combines textual analysis, experiential learning, improvisational performance, and activated writing to ask questions of the relationships between sound, land, and colonial institutions. How does movement through space, and hearing the land, affect our experience of discussing texts? How is discussion informed by, say, the participants being separated (or connected) by a river? What richness exists in oral/aural exchanges that are lost in the textualizing process? What does it mean to move through occupied Blackfoot territory while discussing decolonialism? The structure of this conversational exchange unfolds in loops rather than in the linear standard of academic writing. This “essay” was originally devised as an audiovisual text, but during further revisions, we continued our experimentations with form. The result has taken shape in dual outputs of both sound and text, each form containing affective and sensorial elements not found in the other, creating parallel yet distinct “texts.” While this is an imperfect strategy for those who experience sight/hearing related disabilities, we also recognize that some sensorial experiences are untranslatable into the language of the other senses. We hope that we have encoded each experience of sound and text with enough richness for them to be enjoyed individually, and we invite those who can, to experience how the two forms play off of each other. To this effect, the form of this text focuses on the relationship between the content of our conversation and how it is presented, and between our conversation and the writers, artists and movements we have referenced. We also hope to emphasize our relationality with the land we walked through, the creators of the sounds we listened to, between us, the co-creators of this “text,” as well as the relationship we create with you, the listener/reader experiencing it. As artists/writers/curators, it is a challenge to find alternative textual formats that appropriately reflect artistic research-creation methodologies while also satisfying the demands of academic knowledge dissemination. This collaboration explores the possibility for academic conversations to escape the confines of learning institutions into a space of praxis and embodied experience in motion.
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 | 0.021 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.030 | 0.040 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 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".