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Record W7135966001

Contemporary Book Culture Studies at the Universities in the USA and in Canada

2023· dissertation· cs· W7135966001 on OpenAlexaboutno aff
Petr Matulík

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2023
Typedissertation
Languagecs
FieldArts and Humanities
TopicPhilosophy, History, and Historiography
Canadian institutionsnot available
Fundersnot available
KeywordsCzechContext (archaeology)CurriculumPoint (geometry)Higher educationContemporary historyHistory of education
DOInot available

Abstract

fetched live from OpenAlex

This diploma thesis explores, analyzes, and evaluates forms of contemporary book history education at American and Canadian universities. Its goal is to map book history teaching at these institutions, something that no previous study has addressed in detail. In the theoretical part, the context of book history is presented from a historical point of view based on both Czech and foreign expert literature, with an emphasis on the North American environment and, for comparison, the Czech environment as well. In the practical part, a quantitative and qualitative analysis of individual schools, departments and their programmes where book history can be studied is carried out, based on described context. The main source of information in this case was the publicly available curricula of the institutions, with a supplementary source provided by university representatives, who were contacted when necessary. Based on the analysis, specific trends in contemporary book history education at universities in the United States and Canada are then characterized, summarized and evaluated in the conclusion of the thesis.

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)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.017
Science and technology studies0.0140.006
Scholarly communication0.0080.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.230
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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