Bibliographic record
Abstract
"The Greatest Films" is a poetry manuscript accompanied by a critical essay that explores Indo-Guyanese-Canadian subjectivity in the late 1970s. The poems address themes of cultural hybridity as they are fomented through passages between real and imagined homelands and hostlands. The manuscript employs disjunctive poetic techniques that exteriorize histories of Indo-Guyanese-Canadian cultural and ethnic dispersal and encampment. While by no means an exhaustive list of sources, "The Greatest Films" assembles poems from timelines, cinematic language, letters, lyrical flourishes, oral histories, and world literature. "The Greatest Films" revivifies these sources into repeating lines of verse that pulls readers back-and-forth from the left to right margin with tentative stops in the centre of the page. Regardless of which direction the poems pull readers towards, what always awaits them is an encounter with the residual nostalgia for 'origins' activated by narrative fragments of embroidered ancestral memory before --and distant from--Guyana and Canada.
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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 | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.114 | 0.013 |
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".