Alternative Paths: Mapping Addiction in Contemporary Art by Landon Mackenzie, Rebecca Belmore, Manasie Akpaliapik, and Ron Noganosh
Bibliographic record
Abstract
Building upon the concept of meeting places, this essay considers intersections between land, place, space, colonialism, art, and addiction in the contemporary Canadian context. Examining the work of several artists, both Indigenous and non-Indigenous, the author employs the land-based metaphor of alternative paths to demonstrate how these artists have produced artworks that transcend and resist outgoing negative stereotypes related to addiction and Indigenous individuals. Artistic strategies chosen by the artists include tracing the oral histories of an Indigenous woman onto a map (Landon Mackenzie), occupying place and space with the artist’s own body (Rebecca Belmore), using materials from the land to evoke a head-splitting hangover (Manasie Akpaliapik), and employing irony in order to reveal that both alcohol and humour can function as survival strategies for Indigenous peoples (Ron Noganosh). Ultimately, the essay is intended to destabilize and dislodge stereotypical images of addicted (or ostensibly addicted) individuals in Canada. Furthermore, the fact that recovery from addiction does and will continue to occur in Indigenous communities is inextricably linked with the concepts of empowerment, well-being, and self-determination for Indigenous peoples.
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 | 0.003 | 0.003 |
| Science and technology studies | 0.024 | 0.024 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".