Bibliographic record
Abstract
This PhD in agronomy and environmental sciences, conducted under the joint supervision of UQAM and AgroParisTech on two study areas (Paris, France and Montreal, Qc, Canada) focuses on the analysis of the food function of a non-professional form of urban agriculture: urban collective gardens. It focuses on the importance of this food function from the point of view of gardeners, among other functions they attribute to the gardens, and aims to provide quantified data on gardens’ products. The premise of the thesis is a postulate of coherence between the functions assigned to the gardens by gardeners, their cropping practices and productions of their gardens. The thesis aims therefore at describing these three components and their interrelationships. After defining the research question related to the state of the art on urban agriculture and collective gardens, we discuss the selected methodologies that combine semistructured and structured interviews (questionnaires) with a sample of gardeners in eight gardens of Paris and Montreal, field observation on gardeners cropping practices and measurement of plots production. The results are presented in four chapters. We first show the diversity of regulations that apply to collective gardens, and the recommendations they contained intended to frame the practices of gardeners, highlighting the conflicting aspects that may exist from one regulation to another or even within a regulation. Secondly, we show the complexity of the food function of collective gardens, the central role it plays in the motivations expressed by gardeners and its links with other functions of the gardens. Thirdly, we describe and organize the analysis of gardeners’ cropping practices; we show that they are varied but their consistency can be revealed by the construction of a typology. We then link this typology and the functions assigned to the gardens. We show that the importance given to the food function is correlated to the intensity level of practices, even though gardeners also orientate their practices in respect to other functions they attribute to the garden. Finally, the last chapter of results presents data on production levels in the gardens: we see varying yields and highlight one of the important determinants of yields, namely the intensity of land use. We conclude on the importance of deepening this study of garden productions and related cropping practices after discussing the methodological contributions of the thesis and the limits of our approach.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".