MétaCan
Menu
Back to cohort
Record W2214753061 · doi:10.33137/q.i..v35i2.23623

Eat, Pray, Buy a House: Utopian Visions of Italy in the New Millennium

2015· article· en· W2214753061 on OpenAlexvenueno aff
Cristina Perissinotto

Bibliographic record

VenueQuaderni d italianistica · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsMemoirVisionBeautyDreamArtMateriality (auditing)HistoryAestheticsArt historyLiteratureSociologyAnthropologyPsychology

Abstract

fetched live from OpenAlex

This article explores the peculiar combination of literary memoir, utopian dream and material culture that sprung from a number of books written about Italy (living in Italy, buying a home in Italy, moving back to Italy) in the new millennium. The famous <i>Under the Tuscan Sun</i>, published in 1996, constitutes one of the earliest and most famous examples of this new genre. According to the Tuscan Sun book, it is not longer enough to travel somewhere, but the traveler needs to commune with the land by owning a piece of it. While relatively new, this particular sub-genre, defined by a critic “brick and mortar travel memoir,” has yielded insightful analyses about travels and the encounters with the other in the 21st Century. Memoirs about living, as foreigners, in contemporary Italy are weaved with the utopian dream of finding something in Italy something real: a real sense of community, real food, real feelings, plus a landscape where human interventions have been gentle and capable of creating real beauty. The article examines a number of memoirs written in recent years about Italy. This analysis is conducted primarily from the point of view of utopian studies, but it also explores issues of authenticity and materiality, thereby offering an analysis of the way Italy is nowadays perceived, imagined and idealized in contemporary travel literature.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.266
Teacher spread0.215 · 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.

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueQuaderni d italianisticaSame topicTravel Writing and LiteratureFrench-language works237,207