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Record W3020235149 · doi:10.3167/armw.2019.070106

Destination Museum

2019· article· en· W3020235149 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

VenueMuseum Worlds · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsNothingQueen (butterfly)PopulationHistoryImmigrationWorld War IIArtAncient historyArt historyDemographySociologyArchaeology

Abstract

fetched live from OpenAlex

What was the first museum you remember visiting? I was born in September 1942 during the war. My parents came from Poland. Three weeks after I was born, 6,500 Jews from my father’s hometown, Opatów (Apt, in Yiddish), 65% of the population, disappeared overnight. All but 500 were sent to the Treblinka death camp, and the rest to a forced labour camp. So I grew up in an immigrant neighbourhood in the immediate postwar years. I went through an ultra-Orthodox period (my parents were horrified). I became not only strictly kosher, but also I observed the Sabbath very strictly. That meant I could not ride, spend money, turn on the radio, write, tear paper . . . I could do almost nothing. Except . . . I could walk to the Royal Ontario Museum. . . . and I did. So this was before the era of helicopter parents. At the age of 10, 11, 12 years old, I would walk out of my house, through Queen’s Park, to the ROM, and that was my beloved childhood museum.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.999

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)0.0110.002

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 head0.069
GPT teacher head0.219
Teacher spread0.149 · 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