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Record W2000488415 · doi:10.4018/jdls.2012040104

Are E-Books Making Us Stupid?

2012· article· en· W2000488415 on OpenAlexaff
Nancy McCormack

Bibliographic record

VenueInternational Journal of Digital Library Systems · 2012
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsQueen's University
Fundersnot available
KeywordsReading (process)The InternetPoint (geometry)CarrElectronic bookWorld Wide WebLibrary scienceComputer scienceInternet privacyMedia studiesSociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

In 2008, Nicholas Carr published a provocative article titled “Is Google making us stupid?” in which he ponders the effect of the internet and electronic sources generally on the brain. This paper discusses one source specifically, e-books, and explores whether libraries are acting wisely by moving from print to electronic book collections. The topic is considered from the vantage point of the library and from that of the patron. Specifically, the prospect of an all or largely all e-book future is considered and whether that future means an end to traditional library collections and services. The potential problems for “deep reading” are also considered, and, specifically, whether e-books can serve as an adequate substitute for patrons who will no longer be able to use electronic collections in the way they once used print. In short, this paper explores whether e-books are making us—librarians and patrons—stupid.Request access from your librarian to read this article's full text.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.892
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0030.022
Open science0.0010.000
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 head0.024
GPT teacher head0.236
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2012
Admission routes1
Has abstractyes

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