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Record W2964541081 · doi:10.5931/djim.v15i0.8979

Bitesize: Exploring the Form, Function, and Future of Online Book Summary Services

2019· article· en· W2964541081 on OpenAlexaffvenue
Conor Falvey

Bibliographic record

VenueDalhousie Journal of Interdisciplinary Management · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicPublishing and Scholarly Communication
Canadian institutionsDalhousie University
Fundersnot available
KeywordsFunction (biology)MainstreamReading (process)AppealComputer scienceWorld Wide WebValue (mathematics)Focus (optics)Data scienceInternet privacyPolitical science

Abstract

fetched live from OpenAlex

Popular book summaries are an under-researched family of information objects. Online book summary services offer condensed versions of popular press non-fiction books, especially titles related to management and leadership, for busy readers willing to pay subscription fees. These summaries are intended to be mobile, electronic, quickly-digested alternatives to reading entire books. Summaries can function as tools of learning as well as aids to book discovery. This paper describes the offerings of three online book summary services. It then discusses the implications of such services for information in society. It considers the benefits and drawbacks of the choice to focus these services on popular press nonfiction, which has commercial value and mainstream appeal, rather than other knowledge sources which might be more robust but less desirable to readers. Finally, it examines the ways in which artificial intelligence and natural language processing technologies could transform and disrupt the current system of producing and consuming book summaries.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.673
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.237
Teacher spread0.219 · 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 teacher head, 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
Published2019
Admission routes2
Has abstractyes

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