Ageing and materialities: A study of the practice of weaving at Cercle de Fermieres
Bibliographic record
Abstract
This thesis examines the weaving practices of the Cercle de Fermieres, a century-old community of older women, in light of Actor-Network Theory (ANT) (Akrich, 1987; Latour, 2006) and feminist theories of technologies (Haraway, 2004; Wajcman, 2007). Who and what is included in this “Cercle?” How do the affordances of technologies and materials contribute to the creation of necessities and forms of interaction within the organization? What happens when both humans (weavers) and non-humans (looms, thread, buildings) actors “age together?” I examine how the dynamic assemblage pertaining to the practice of weaving influences the organizational structure of the Cercle and contributes to the creation of associations and entanglements. Five vignettes describe life at the weaving Cercle and the roles of actors and ageing in this organization. A relational understanding of age and ageing, essential components of this analysis, allows to notice their uneven effects across the assemblage. While ageing has a profound impact on what it means to be a weaver, a centenarian organization or an ageing technology, ANT provides few theoretical tools to comprehend these entangled issues. This is addressed in the discussion section of this thesis. The empirical data comes from interviews and participant observation of two Cercles de Fermieres : one in Montreal and one in Baie Saint-Paul. Interviews were conducted with five Fermieres, aged 80 years old or more.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.022 | 0.022 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".