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Record W4387879044 · doi:10.1080/00751634.2023.2261310

Matera <i>in posa</i> : The Photographic Self-Portrait of a Southern-Italian City, 1900–1920

2023· article· en· W4387879044 on OpenAlexaff
Mark Russell

Bibliographic record

VenueItalian Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicItalian Fascism and Post-war Society
Canadian institutionsConcordia University
Fundersnot available
KeywordsPortraitScholarshipNarrativeRepresentation (politics)Framing (construction)Context (archaeology)PhotographyVisual artsHistoryArtArchaeologyPolitical scienceLiteraturePoliticsLaw

Abstract

fetched live from OpenAlex

Photography has played an important role in framing popular perceptions of Matera. Scholarship has focused on its representation following 1945. Yet the fact that a photographic portrait of Matera existed before this time is often overlooked. Photographs of the city pre-dating 1920 were mostly published as postcards by local entrepreneurs. This article analyzes a selection of these in the context of evolving representations of Matera and Basilicata in the early twentieth century. Providing insight into the aesthetic and socio-cultural construction of this important aspect of the city’s early photographic portrait, it emphasises that postcards issued by local enterprises offered a perspective on Matera and Basilicata from the publisher’s point of view. They complemented a less prejudiced and sometimes positive portrayal of the region – emerging in a variety of texts, photographs, and public events – that modified narratives often narrowly focused on describing it as impoverished, backward, and isolated.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.310
Teacher spread0.275 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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