Bibliographic record
Abstract
The intention of this thesis project will be primarily focused on issues of the cemetery that involve its utilization as a vehicle to cultivate an awareness of heritage and its role in establishing a framework on which to promote the sense of communal identity in an authentic manner. For as many divergent societies that co-exist on earth there are equally as many diverse ritualistic patterns involving death and dying particular to each society. Although the study of these ritualistic patterns is an intriguing one, with regard to utilization of the cemetery as a vehicle to strengthen the identity of place, I believe, it is essential to accommodate and enrich already accepted notions of death and dying particular to Vancouver and Canada. As a consequence of the country's age, it seems that there is always the pressure to import character and values from other places. To begin to define an identity and therefore cultivate community there has to be acknowledgment and acceptance of heritage as an initial point of growth. For these reasons, rather than replace an already existing set of rituals with foreign ideologies surrounding death and dying, it is crucial that existing rituals not be discarded. The proposed site for this project is the Grandview Cut rail corridor that extends between the False Creek Flats and Grandview Woodlands in East Vancouver. Specifically, the site is situated between Clark Drive on the west and Slocan Drive on the east.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.074 | 0.006 |
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".