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Record W3210937173 · doi:10.22148/001c.29802

Audiobook Stylistics: Comparing print and audio in the bestselling segment

2021· article· en· W3210937173 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Cultural Analytics · 2021
Typearticle
Languageen
FieldComputer Science
TopicAuthorship Attribution and Profiling
Canadian institutionsnot available
Fundersnot available
KeywordsStylisticsDepictionFocus (optics)Point (geometry)Style (visual arts)Set (abstract data type)Plot (graphics)Computer scienceAdvertisingArtLiteratureMathematics

Abstract

fetched live from OpenAlex

The paper explores differences between bestsellers in print and the most popular audiobooks in a subscription-based streaming service for books ('beststreamers') by means of computational stylistics. The point of departure is the complete set of print bestsellers and digital audiobook beststreamers for the Swedish book market 2015–2019, in total 172 novels. We probed 34 linguistic measures to track differences between subsets at the stylistic level. The results indicate that there are pronounced differences between the formats. Print bestsellers are longer, syntactically more complex and varied, and seem to focus more on depiction. Beststreaming audiobooks, by contrast, are shorter, more straightforwardly written, and appear to highlight plot and dialogue. The results are replicated when the comparison is restricted to crime fiction, the most prominent genre in the commercial top segment. Given these results, it is argued that it is possible to discern a particular audiobook style as one factor affecting book consumption in digital formats, and conversely that the printed format is associated with other stylistic preferences.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.698
Threshold uncertainty score0.243

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 communication0.0000.000
Open science0.0000.000
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 head0.069
GPT teacher head0.306
Teacher spread0.237 · 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