An A/r/tographic Inquiry of a Silenced First Nation Ancestry, Hauntology, G(hosts) and Art(works)
Bibliographic record
Abstract
As a hauntological artist, I deconstruct my silenced First Nation Wolastoqiyik (Maliseet) ancestry and look towards the intergenerational narratives of my grandmother, mother, and I. Employing the methodology of a/r/tography, the intersection of autobiography and art-making, I utilize diverse art forms to find that g(hosts) reside amongst spaces of liminality. Supported by the methodology of a/r/tography and drawing upon works, which blur the boundary between past and present, self and other, I deconstruct the silencing of my First Nation lineage by creating three art(works). These art(works) are placed within an exhibition catalogue and inquire into 1) the specters that loom between the evocative objects of our narratives, 2) how script-writing and the script’s performance can reveal ghosts in spaces of liminality, and 3) how sculptures facilitate spectral movement. Each individual art(work) plays a role in breaking the silence. A(wake), specters arise.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".