MétaCan
Menu
← Back to cohort
Record W4414153784 · doi:10.1201/9781003260585-60

National identity in the presidential addresses of 10 June, between 1977/1978 and 2006 – creation, transformation, and metamorphosis

2025· book-chapter· en· W4414153784 on OpenAlexfundno aff
Ana Lúcia Da Silva Reis

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaFederation for the Humanities and Social Sciences
KeywordsNational identityPresidential systemPortugueseIdentity (music)DemocracyIdeology

Abstract

fetched live from OpenAlex

This article focuses on 29 (of a total of 45) presidential addresses delivered over the first thirty years of the post 25 th of April democratic era, on the National Day of Portugal on June 10 th . These speeches were given during the administrations of the following Portuguese presidents, who each served two terms between 1976 and 2006: Antonio Ramalho Eanes, Mário Soares, and Jorge Sampaio. The addresses are analyzed in terms of identity categories ( Thiesse, 2000 ) which the speakers used when they refer to national identity. With this analysis I intend to determine which references to historical moments, illustrious figures, national heroes, and mentalities contribute to the construction of a collective ideology in which the Portuguese people can visualize themselves. On the suggestion of the organizers of this conference this study will be articulated with the concepts of creation, transformation, and metamorphosis of national identity over the course of the first 30 years of democracy in Portugal.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0050.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.052
GPT teacher head0.295
Teacher spread0.243 · 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 designQualitative
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicTranslation Studies and Practices→French-language works237,207→