Bibliographic record
Abstract
Throughout history, farm families have shared work and equipment with their neighbours to complete labour-intensive, time-sensitive, and time-consuming tasks. They benefitted materially and socially from these voluntary, flexible, loosely structured networks of reciprocal assistance, making neighbourliness a vital but overlooked aspect of agricultural change. Being Neighbours takes us into the heart of neighbourhood – the set of people near and surrounding the family – through an examination of work bees in southern Ontario from 1830 to 1960. The bee was a special event where people gathered to work on a neighbour’s farm like bees in a hive for a wide variety of purposes, including barn raising, logging, threshing, quilting, turkey plucking, and apple paring. Drawing on the diaries of over one hundred men and women, Catharine Wilson takes readers into families’ daily lives, the intricacies of their labour exchange, and their workways, feasts, and hospitality. Through the prism of the bee and a close reading of the diaries, she uncovers the subtle social politics of mutual dependency, the expectations neighbours had of each other, and their ways of managing conflict and crisis. This book adds to the literature on cooperative work that focuses on evaluating its economic efficiency and complicates histories of capitalism that place communal values at odds with market orientation. Beautifully written, engaging, and richly detailed and illustrated, Being Neighbours reveals the visceral textures of rural life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.015 |
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".