British Columbia beekeeping revenues and costs: survey data and profit modeling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
British Columbia beekeepers, like many beekeepers around the world, are currently facing declines in honey bee health and high overwinter colony losses. To better understand the economics and the cycle of yearly colony loss and replacement of this critical agricultural industry, we collected and analyzed survey data on beekeeping costs and returns. Forty British Columbia beekeepers provided details about revenue sources, variable costs, capital costs, and investments. Ten surveyed beekeepers managed between 1 and 9 colonies, 10 managed between 10 and 39 colonies, 9 managed between 40 and 100 colonies, 5 managed between 101 and 299 colonies, 3 managed between 300 and 699 colonies, and 3 managed 700 colonies or more. The data was used to calculate beekeeping profit and to parameterize a model that explores the economic impact of colony loss rates and replacement strategies. Survey results show that when the data is aggregated, revenues exceed costs for beekeeping operations in British Columbia with a per colony profit of $56.92 or $0.87 per pound of honey produced. Surveyed operations with fewer than 100 colonies have negative profits, while operations with 100-299 colonies have positive profits. Surveyed operations in the Cariboo, North Coast, and Okanagan regions have the highest profits while surveyed operations in the Peace region have the lowest profits. Profit modeling shows that replacing losses with packages generates lower profit than replacing losses with split colonies. Our modeling shows that operations that diversify their revenue to include bee sales and commercial pollination accrue higher profits and can withstand higher winter loss rates.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it