Bibliographic record
Abstract
Traverser les frontieres geographiques et litteraires La journaliste, ecrivaine et editrice d’origine roumaine Felicia Mihali se penche sur sa vie et ses oeuvres, ou evoluent des personnages feminins a l’identite hybride qui voyagent entre la Roumanie et le Canada, entre plusieurs langues et plusieurs disciplines comme l’histoire et la politique. A travel across geographical and literary borders This interview to the journalist, author and editor Felicia Mihali explores her life, her novels, the hybrid identity of her feminine characters and her narrative spaces in balance between Romania and Canada, amidst languages, history and politics. Attraversare le frontiere geografiche e letterarie L’intervista alla giornalista, scrittrice ed editrice Felicia Mihali, ne percorre vita e opere, mettendo in evidenza i personaggi femminili, caratterizzati da identita ibrida, e gli spazi narrativi in equilibrio tra Romania e Canada, tra piu lingue e piu dimensioni, come quella storica e politica. DOI: 10.1400/272690
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
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".