Farm Income, Financial Conditions and Government Assistance - Data Book
Bibliographic record
Abstract
The purpose of this data book is to provide easy access to key economic and financial indicators for the farm sector and information on government assistance to the agriculture and agri-food sector. The information is prepared in consultation with the provincial ministries responsible for Agriculture. Assistance is also provided by other members of Agriculture and Agri-Food Canada as well as by officials in other federal and provincial departments. The data book is divided into four sections. Section A presents information related to farm income. Section B contains information on farm financial conditions. Section C provides data on government expenditures for the agri-food sector. Section D provides information on estimates of support to agriculture. Notes on the methodology are provided at the end of each section. This issue provides the most up-to-date key economic and financial indicators. Electronic Updates for 2008 This electronic update covers sections A, B, and C of the December 2008 data book. In these sections only the tables and figures for which we had new information along with highlights are provided. The methodology notes appearing at the end of each section of the December 2008 data book will be reviewed only in 2009 when a new version of the entire data book is scheduled to be produced. In the meantime, users can refer to the methodology notes of the December 2008 data book. The purpose of the data book electronic updates is to provide easy access to key economic and financial indicators for the farm sector and information on government assistance to the agriculture and agri-food sector. The information is prepared in consultation with the provincial Ministries of Agriculture. Assistance is also provided by other members of Agriculture and Agri-Food Canada as well as by officials in other federal and provincial departments.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.150 | 0.139 |
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".