Land Matters: Stories of Survival, Peasant Roots & Peasant Futurisms
Bibliographic record
Abstract
Combining my literary writing practice with academic research, this doctoral research-creation project reads ecological and social violence as “one phenomenon” caused by early capitalism and intensifying after the industrial revolution in 1850, and especially after the neoliberal tide post-1945 (Moore 120-136). My project responds to the social, ecological and climate crisis subjectively, from my situated knowledge. As a type of life writing that tends toward autotheory, the “Stories of Survival” section deconstructs narratives of empire building, colonization, nation-state borders of exclusion, and the often-traumatic experiences of a refugee, illegal immigrant, and temporary guest who immigrated to Canada not by choice, but as an act of survival. This opening section is told from the point of view of my (severed) relationship to land and sets the narrative and theoretical context for the next two chapters. Disillusioned by my stories of survival, the “Peasant Roots” chapter returns to my ancestral past and explores the life of my Bosniak (Muslim Bosnian) peasant grandparents through knowledges, values, and practices of subsistence farming and self-sustainability; local gift, barter and exchange economies; the čaršija (farmers’ market) as a mechanism for local economies (Lockwood 120); komšiluk (neighbourhood life), halal exchange, and collaborative labour as practices of mutual aid (Henig 3); the zadruga (multigenerational household) and peasant minimalism (Barić 3-7). From these peasant roots, I articulate a kind of re-enchantment through an alternative futurity which I call “Peasant Futurisms.” So as not to reproduce white supremacy and other forms of domination, this subaltern world-building project is a work of political art meant to be taken up by members of what Fred Moten and Stefano Harney call “the undercommons,” including Black, Indigenous, queer, trans, poor, disabled and peasant folk. As a nexus of neoliberal power, cities and urban lifeworlds represent patterns of power, capital, and nature that must be challenged. Peasant Futurisms challenges capitalist cities built for cars and big commerce by sketching edible and wilder ecocities surrounded by protected greenbelts and peasant/regenerative organic farmer belts within local cyclical economies.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.033 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".