« Rencontre avec Naomi Fontaine » de la semaine de la francophonie organisée par Catherine Lamaison
Bibliographic record
Abstract
Naomi Fontaine s’est adressée à une quarantaine de participants réunis en ligne pour nous présenter ses trois récits : Kuessipan. Mémoire d’encrier, 2011; transl. David Homel: Kuessipan. Arsenal Pulp Press 2013; Manikanetish. Mémoire d’encrier, 2013; trad. David Homel: Tshinanu. Granta #141, special: Canada Septembre 2017, pp. 279–285; (en allemand et français) trad. Sonja Finck: Tshinanu. dans Jennifer Dummer éd.: Pareil, mais différent - Genauso, nur anders. Frankokanadische Erzählungen. Bilingue. dtv, Munich 2020, pp 92–109 ; et Shuni. Mémoire d’encrier, 2019 (gagnante pour le « Prix littéraire des collégiens », 2020), tous publiés chez Mémoires d’Encrier : http://memoiredencrier.com/naomi-fontaine/
 Naomi Fontaine retrace son parcours d’écrivaine avec nous.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 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 teacher head, 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".