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Record W6959056506 · doi:10.7910/dvn/3cycb

Senate Unpassed Legislation 1839, Docket 10525, SC1/series 231, Petition of Ruth Bowker

2017· dataset· en· W6959056506 on OpenAlexaboutno aff

Bibliographic record

VenueHarvard Dataverse · 2017
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationSubject (documents)House of RepresentativesPoliticsEndowmentLegislature

Abstract

fetched live from OpenAlex

Petition subject: To abolish slavery in Washington D.C. Original: http://nrs.harvard.edu/urn-3:FHCL:11858079 Date of creation: (unknown) Petition location: Sudbury Legislator, committee, or address that the petition was sent to: Jeremiah Spofford, Essex; committee on the subject Selected signatures: Ruth Bowker Polly Brown Lucy B.A. Browne Actions taken on dates: 1839-01-17,1839-01-17 Legislative action: Received in the Senate on January 17, 1839 and referred to the committee on the subject and sent for concurrence and received in the House on January 17, 1839 and concurred Total signatures: 72 Legislative action summary: Received, referred, sent, received, concurred Female signatures: 72 Female only signatures: Yes Identifications of signatories: undersigned, [females], ["women"] Prayer format was printed vs. manuscript: Printed Additional non-petition or unrelated documents available at archive: no additional documents Location of the petition at the Massachusetts Archives of the Commonwealth: Senate Unpassed 1839, Docket 10525 Acknowledgements: Supported by the National Endowment for the Humanities (PW-5105612), Massachusetts Archives of the Commonwealth, Radcliffe Institute for Advanced Study at Harvard University, Center for American Political Studies at Harvard University, Institutional Development Initiative at Harvard University, and Harvard University Library.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: Dataset · Consensus signal: none
Teacher disagreement score0.760
Threshold uncertainty score0.801

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.2400.135

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 head0.020
GPT teacher head0.229
Teacher spread0.210 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2017
Admission routes1
Has abstractyes

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