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Record W4388462620 · doi:10.1515/9783110753523-010

The Literary System of the Iberian Worlds Through the Lens of Criticometrics

2023· book-chapter· en· W4388462620 on OpenAlexaboutno aff
Carolina Ferrer

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMedieval Iberian Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLens (geology)GeographyArtGeologyPaleontology

Abstract

fetched live from OpenAlex

The Iberian worlds are constituted by the group of people whose culture and history were forged when the matrix of the Mediterranean world was projected through the Portuguese and Spanish expansion.The populations that are protagonists of this process (Europeans, Africans, Americans, and Asians) and their descendants share a common experience and a way of conceiving the world (Ruiz Ibáñez y Mazín Gómez 2021:2). 1 The purpose of our study is to map the literatures that belong to the above defined Iberian worlds, in order to reveal the complex relations that the national literatures that constitute these worlds have developed through time.To this effect, this research is located at the convergence of two phenomena: the conceptual turn from comparative literature into world literature (Damrosch 2014;Gupta 2009;Saussy 2006), and the emergence of big data in the humanities (Boyd and Crawford 2012; Mayer-Schönberger and Cukier 2013; Schreibman, Siemens, and Unsworth 2004, 2016).Specifically, in this paper, we will illustrate how this availability of massive amounts of information for the humanitiesunimaginable not long agowill allow us to analyze the configuration of the literary system of the Iberian worlds.We would like to emphasize that, in this research, we modify the usual topdown viewpoint to introduce a bottom-up perspective.To achieve this, we use the methodological approach of criticometrics (Ferrer 2011), that we have developed based on the exploitation of digital databases and which makes it possible to articulate theoretical concepts with empirical research.Instead of imposing pre-established criteria, this approach stems from the observation of thousands of Note: This study draws on research funded by the Social Sciences and Humanities Research Council of Canada, granted to the CRSH 435-2018-1115 project « Les études littéraires et les nouveaux observables de l'ère numérique : le système de la littérature mondiale de l'après-guerre à nos

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: Other
Teacher disagreement score0.922
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.246
Teacher spread0.162 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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