What is the Libano-Québécois? Representing the Migrant Subject in Québec National Cinema
Bibliographic record
Abstract
This article analyzes how a body of twenty-first-century Québécois films featuring Lebanese (or Syrian) protagonists construct the migrant subject in relation to place and gender. It examines how its corpus—Wajdi Mouawad’s Littoral (2004), Ivan Grbovic’s Romeo Onze (2011), Samer Najari’s Arwad (2013) and three films by Maryanne Zéhil, De ma fenêtre sans maison (2006), La vallée des larmes (2012), and L’autre côté de novembre (2016)—portrays male or female protagonists experiencing identity crises as they negotiate the entre-deux , the in between, of migrant identities. These films represent what Homi K. Bhabha has called “third space interventions” by (mostly) migrant filmmakers and they seek to combat what has been identified as a “state-sponsored amnesia” about the Lebanese Civil.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".