MétaCan
Menu
Back to cohort
Record W4403959858 · doi:10.1515/9781478060116

Landbridge

2024· book· en· W4403959858 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicCivil and Structural Engineering Research
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

In 1980, Y-Dang Troeung and her family were among the last of the 60,000 refugees from Cambodia that Canada agreed to admit. Their landing was widely documented in newspapers, with photographs of the prime minister shaking Troeung’s father’s hand and patting baby Y-Dang’s head. Troeung became a literal poster child for the benevolence of the Canadian refugee project. She returns to this moment forty years later in her arresting memoir Landbridge , where she explores the tension between that public narrative of happy “arrival,” and the multiple, often hidden truths of what happened to her family. In precise, beautiful prose, Troeung moves back and forth in time to tell stories about her parents and two brothers who lived through the Cambodian genocide, about the lives of her grandparents and extended family, about her own childhood in the refugee camps and in rural Ontario, and eventually about her young son’s illness and her own diagnosis with a terminal disease. Throughout this brilliant and astonishing book, Troeung looks with bracing clarity at refugee existence and dares to imagine a better future, with love.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.011
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.007
GPT teacher head0.201
Teacher spread0.194 · 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