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Record W7127411767 · doi:10.14672/se.v3i2.3070

Book Price Dynamics, Publication Date, and Concentration in the Italian Book Market. A Descriptive Exploration of the Italian and Foreign Fiction Books, 2022-2025

2025· article· en· W7127411767 on OpenAlexaboutno aff
Antonello E. Scorcu

Bibliographic record

VenueArchivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPeriod (music)Ranking (information retrieval)Quarter (Canadian coin)Price index

Abstract

fetched live from OpenAlex

This paper examines some characteristics of the Italian book market. Monthly data published by Il Giornale della Libreria, using NielsenIQ BookData, offers a detailed and timely analysis of the 100 best-selling books in the main market segments. Our analysis focuses on Italian and foreign fiction and evaluates the recent dynamics of price, publication date, and sales concentration from January 2022 to August 2025. Over this period, the average price of the 100 most-read Italian and foreign fiction books remained virtually constant in nominal terms, with some seasonal fluctuations. The average price of foreign fiction books is slightly higher than the average price of Italian fiction books. In both segments, the average age of the 100 best-selling books (calculated as the difference between the entry date in the monthly ranking and the publication date) remains virtually constant over the period examined. The age of foreign fiction books is higher than that of Italian fiction books. Temporary variations are also observed, with age decreasing in the last quarter of the year. Finally, the concentration of sales does not reveal any significant pattern.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.878
Threshold uncertainty score0.658

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 studies0.0010.001
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.200
Teacher spread0.185 · 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
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
Published2025
Admission routes1
Has abstractyes

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