Des nouveaux.elles Italiens.nes à Montréal : Histoires de migrations dans les carrefours de la mobilité
Bibliographic record
Abstract
Dans cette recherche, neuf participant.es d’origine italienne venu.es à Montréal après 2007 reviennent sur leur parcours migratoire. La structure du récit découpe leur trajet en fonction du lieu d’origine et des lieux de passage dans différentes villes pour s’intéresser à l’impact de l’expérience dans celles-ci sur le type d’installation qu’ils.elles choisissent : temporaire ou permanente. En faisant cette lecture de la trame narrative autour de leur type de mobilité, le sens du (des) lieux pour chacun d’eux.elles, fait ressortir des rapports d’attachement ou de répulsion aux lieux qui orientent et ponctuent les changements d’installation au fil du temps. La recherche aborde également leur rapport à la ville de Montréal en observant l’effet de la présence de la communauté italienne sur leur installation qu’elle soit de longue ou de courte durée. La plupart du travail de recherche, dont les entrevues et les contacts avec les participant.es, ont été réalisés entre 2015 et 2018 soit avant l’événement de pandémie de COVID-19. \n \nIn this research, nine participants of Italian origin who came to Montreal after 2007 reflect on their migratory journey. The structure of the narrative divides their journey according to the place of origin and the places of passage in different cities to focus on the impact of the experience in these on the type of installation they choose: temporary or permanent. By doing this reading of the narrative framework around their type of mobility, the sense of the place(s) for each of them brings out the relationships of attachment or repulsion to the places which orient and punctuate the changes of installation over time. The research also addresses their relationship to the city of Montreal by observing the effect of the presence of the Italian community on their settlement, whether long or short. Most of the research work, including interviews and contact with participants, was carried out between 2015 and 2018, before the COVID-19 pandemic event.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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".