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Record W4220853898 · doi:10.1177/02656914221085129

‘Living Normally’: Everyday Life Under Salazarism

2022· article· en· W4220853898 on OpenAlexfundno aff
Daniel Melo

Bibliographic record

VenueEuropean History Quarterly · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHistory, Culture, and Society
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaFederation for the Humanities and Social Sciences
KeywordsDictatorshipEveryday lifeNegotiationCivil societySociologyResistance (ecology)Movie theaterSociocultural evolutionReading (process)State (computer science)Media studiesMass mediaPopular culturePolitical scienceGender studiesSocial scienceLawPoliticsArtLiteratureAnthropology

Abstract

fetched live from OpenAlex

In this article we propose a problematizing overview of daily life under the Salazarist dictatorship (1926–1974), linking the corporative, educational and propagandistic contexts. We examine how institutionalized, controlled, negotiated and/or repressed leisure was spread throughout the smallest interstices of daily life in Portugal. We also analyse the dichotomous realities and policies for the people and elites (in education and reading, cultural production, circulation and consumption), for women and men (social and cultural roles), etc., and compromises with an expanded mass culture. The article directs attention to specific examples of sociocultural negotiations between civil society and the state, as happened in sports (para-)folkloristic festivities and parades (e.g. the ‘popular marches’) and in certain mass culture productions (e.g. revue theatre, cinema, broadcasting and television). Similarly, our ‘bottom-up’ approach focuses on evidence of subversive or alternative sociability and cultural achievements, demonstrating that, in some areas, elements of civil society were able to express open resistance and/or alternative views to the dictatorship.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.649
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0140.004

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 head0.047
GPT teacher head0.293
Teacher spread0.246 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

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