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Record W6962836307 · doi:10.17026/dans-zsu-xavf

The Allen Unger Commodities Dataset

2018· dataset· en· W6962836307 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDANS Data Station SSH · 2018
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAbu dhabiPeriod (music)Research councilFoundation (evidence)WelfareWorld trade

Abstract

fetched live from OpenAlex

The Database presents price data, published in the nineteenth and twentieth centuries, in machine-readable form. The original goal was to examine changes in prices and their relation to international trade in early modern Europe. Price series were then expanded from just staple grains and beyond a limited number of years to the entire period ranging from the earliest known series from the High Middle Ages and down to 1914. The geographical range as well as that of commodities continues to expand with continued research and coding of published data. With the larger collection of figures studies of market integration as well as welfare of consumers and other topics has become possible. Continuing support from the Social Sciences and Humanities Research Council of Canada, the National Science Foundation of Britain, the British Academy and NYU Abu Dhabi has made possible the addition of new data and refinement of existing files.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient 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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0070.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.029

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 head0.097
GPT teacher head0.365
Teacher spread0.268 · 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

Quick stats

Citations1
Published2018
Admission routes2
Has abstractyes

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