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Record W7024693967

Speaking Volumes: Publishers’ Bindings in English-Canada 1870-1920

2020· dissertation· en· W7024693967 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2020
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicNonlinear Waves and Solitons
Canadian institutionsnot available
Fundersnot available
KeywordsPublishingState (computer science)Reading (process)Quality (philosophy)Industrialisation
DOInot available

Abstract

fetched live from OpenAlex

The nineteenth century saw a significant shift in how books were produced. Industrialization and the emergence of a mass reading public, whose members also had increased leisure time and money, led to the need for less expensive books than those bound by individual readers. Publishers’ bindings, the specific design created to address this need, also created the modern book, the book as we know it today. These bindings flourished in Britain and the United States between 1820 and 1920, but not in Canada. This thesis will argue that while publishers’ bindings were not as extensive in English Canada between 1870 and 1920 as they were in Britain and the United States, they did exist, as evident in the three case studies: the individual binder James Barry, the businessman John Lovell, and the collection created by Lorne Pierce. Canada, to be sure, experienced the same changes that led to the need for less expensive books in Britain and the United States. Full of potential, a few circumstances unique to Canada nevertheless frustrated and delayed the development of a significant book publishing industry for several decades. Given the state of Canadian publishing circa the 1870s, Canadian authors were forced to seek external publishing outlets for their work. This, in turn limited the need for publishing innovations. Additionally, copyright laws provided further roadblocks to the publishing business in Canada, and subsequently affected the development of a national industry able to match the quantity and quality of its British and American counterparts. Through the use of three case studies, we will see that nonetheless bookbinders and publishers alike sought creative ways to circumvent the challenges and produce these uniform bindings.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.181
Threshold uncertainty score0.950

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0310.011
Scholarly communication0.0150.004
Open science0.0020.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0180.002

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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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