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The War of 1812 in 140 Characters or Less: "SuperCool or Super Un-tweet Worthy?"

2014· article· en· W2164783352 on OpenAlexaboutno aff
Katy Lalonde, Chris Sanagan, Sean P. Smith

Bibliographic record

VenueThe American Archivist · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

The bicentennial of the War of 1812 provided the Archives of Ontario (AO) with a unique opportunity to employ social media to reach new audiences while speaking to the value of the archival record. Over the course of a year, the AO posted the diary entries of Ely Playter, a farmer and officer of the Upper Canada militia on Twitter (@ElyPlayter1812). A dedicated observer and recorder of daily life, Playter left behind an eyewitness account of the war, thereby giving a real voice to its social, economic, political and personal impact. The Twitter feed provided its followers access to historical records on a daily basis and became a cornerstone of related institutional educational programming. This article includes analysis of the project's methodology and provides insight into the challenges and opportunities of using social media to promote the importance of archives and primary source records.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.460
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0110.010
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.025
GPT teacher head0.215
Teacher spread0.189 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations2
Published2014
Admission routes1
Has abstractyes

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