Visual Perceptions and Written Impressions of the First World War at the Time of Portuguese Modernism
Bibliographic record
Abstract
The first conflict on a world-wide scale broke out just as the Modernist Movement in Portugal was taking its first steps. Britain’s resistance towards Portuguese participation in the War, and the exacerbated positions of those in favour and those against it, were reflected in both illustrations and articles published in the periodical press of the day, as well as in later accounts written by the members of the Portuguese Expeditionary Force (CEP). In certain cases, these written and visual narratives deconstructed stereotypes, whilst in others new cultural imagotypes of British allies were created. This article attempts to compare and contrast such deconstructions appearing in memoirs, with visual perceptions and written impressions of the conflict, published in the periodicals of the time. For the purpose of this paper, two, amongst them, have been selected: A Águia, in which Fernando Pessoa made his literary debut and to which several of the collaborators of Orpheu, the emblematic journal of Portuguese Modernism, also contributed; and Ilustração Portugueza, an important record of Portuguese life in the first quarter of the twentieth century, in which Stuart Carvalhais was one of most distinguished contributors
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".