Bibliographic record
Abstract
I created the piece "Red Blindfolds Torn, Eyes Uncovered" during the current escalation of genocide and suffering in Palestine. It captures the moment of rupture — when red blindfolds of denial are torn away, exposing both the horrors of violence and the machinery of political theatre that sustains it. The left side of the image portrays the raw human cost: grief, blood, and survival. The right side unveils the calculated indifference of power, blind allegiance, and spectacle. "Red Blindfolds Torn, Eyes Uncovered" is a visual call to awaken, to witness, and to no longer look away. As a recent University of Saskatchewan graduate, I am grateful for the opportunity to use both research and art as forms of creative and academic expression. Together, they offer different but powerful ways of engaging with the world—research helps us understand and contextualize suffering, while art allows us to feel and respond to it. This piece is a small attempt to speak to the realities that many are forced to endure in silence. It is a privilege to contribute, even in a limited way, to raising awareness and affirming the humanity of those whose stories are often ignored. "Through the Endless Void" is a surreal piece I created about the pervasive reach of surveillance technology in modern times. This artwork depicts two contrasting worlds: a decaying urban landscape with themes of paranoia and loss of privacy, and an alien terrain that reinforces themes of control. At the vanishing point lies an unblinking, omnipresent eye. This eye watches over both sides, implying that even in fantastical worlds, there is no escape. I depict this contrast purposefully to capture the dissonance of modernity, where freedom is overshadowed by constant technological surveillance. This piece serves both as a warning and as a reflection of reality, urging us to question who is watching us.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.021 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".