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Record W7066797295

La promoció de la lectura a les llibreries de Catalunya (2020-2023)

2024· article· ca· W7066797295 on OpenAlexaboutno aff

Bibliographic record

VenueRevistes Científiques de la University of Barcelona (University of Barcelona) · 2024
Typearticle
Languageca
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Quarter (Canadian coin)Latin Americans
DOInot available

Abstract

fetched live from OpenAlex

S’analitza la transformació de les llibreries catalanes durant el període 2020-2023, marcat per l’impacte de la pandèmia de covid. Un dels canvis principals fou la digitalització, amb l’obertura de botigues en línia, inicialment poc freqüent, però esdevinguda essencial. La pandèmia també va reforçar l’autoestima del sector i va posar en relleu la importància de la lectura, amb un augment de vendes i noves iniciatives com Llibreries Obertes, que va permetre la compra de llibres de proximitat durant el confinament. A més, es consolida un model de llibreria petita, sostenible i arrelada al territori, encara que també hi ha llibreries de dimensions mitjanes amb un fort suport inicial. Les llibreries han esdevingut espais culturals dinàmics amb activitats variades, que han contribuït a la cohesió comunitària. En un futur, es destaca la importància d’integrar aliances digitals i analògiques per mantenir la singularitat, proximitat i sostenibilitat del model cultural i econòmic de les llibreries.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.578

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.004

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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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