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Record W7052686828

Shaping Vancouver Series 2018: Contested Places | The Complexity of Places: The Heather Street Lands

2018· other· en· W7052686828 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2018
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)CorporationPlan (archaeology)Order (exchange)Local governmentIndigenous
DOInot available

Abstract

fetched live from OpenAlex

\nHeritage sites very often are much more intricate places than we may realize. In order for them to be appreciated, educational, positively experienced, and inspirational we need to effectively plan for and manage the multiple ways a place is significant to different groups of people.\n\nThe Heather Street Lands is a 21-acre parcel of land, located between 33rd Ave and 37th Ave, intersecting with Heather Street. It is co-owned by the MST Partnership, made up of the Musqueam Indian Band, the Squamish Nation and Tsleil-Waututh Nation, and the Canada Lands Company, a federal corporation that aims to incorporate former Government of Canada sites into the community. This site has different meanings to various groups and organizations around the city. There are many differing values present — cultural, social, historical, architectural, natural, economic — which span the physical and the intangible. There is also a painful history embedded here for First Nations people, with some representatives having requested the removal of a building on this site as a form of reconciliation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.624
Threshold uncertainty score0.748

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.008
Scholarly communication0.0120.003
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0600.005

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.

Opus teacher head0.030
GPT teacher head0.233
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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