Bibliographic record
Abstract
Eurydice constitue le dilemme d’un nom suggestif dans un univers de mystere. Attiree tres jeune par le chant, elle est assidue aux celebrations tenues tous les deux dimanches dans l’eglise de sa section rurale. Elle se souvient confusement des mots de sa mere partie trop vite, qui la rendaient heureuse. Ses sœurs cadettes frequentent l’ecole, sa tâche est de vendre au marche le surplus des recoltes. Malgre le sort injuste reserve a Eurydice, les trois sœurs se considerent une en trois. A Port-au-Prince, le caractere d’Eurydice, la marchande ambulante, lui permet de nouer de solides relations avec Maryse, une nouvelle mamie et madame, une bourgeoise des hauts quartiers. Pour s’etre defendue contre une tentative de viol, elle dut traverser avec dechirement, la frontiere qui mene en Republique dominicaine. Elle y trouvera en la personne du lieutenant Arturo Vega, l’amour qui se concretisera des annees plus tard. A Paris, elle rencontrera sa sœur artistique, l’Africaine Myriam Selese. Montreal deviendra son port d’attache. Chloe l’a rejointe, porteuse d’un terrible secret de nature a perturber l’amour qui les unit. Eurydice restera-t-elle la voix de la diaspora haitienne.
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.870 | 0.790 |
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".