Treating Farms as Firms? the Evolution of Farm Business Support from Productionist to Entrepreneurial Models
Bibliographic record
Abstract
Farming enterprises throughout the European Union have traditionally been treated very differently by the state compared with their nonagricultural counterparts. Agricultural activities have been governed by a separate set of policy objectives, political institutions, and support agencies. However, this agricultural ‘exceptionalism’ is being steadily eroded as markets are partially liberalised, farmers are encouraged to pursue new forms of economic activity, and as government institutions are reformed. Farmers are being encouraged to see themselves as ‘entrepreneurs' to face fundamentally changed markets. There is, therefore, renewed attention to the existing levels of generic business skills within the farming sector and to the nature and effectiveness of business advice and support frameworks in enhancing these skills. The paper investigates the extent to which farmers have experienced different patterns of business support use and perceive themselves as having different generic skills needs in comparison with other rural microbusinesses and considers the attractiveness of different models of delivering business advice to the sector. A review is undertaken of the evolution of rural business support in England together with an analysis of data from a survey of almost 1800 rural microbusinesses in the northeast of England. It is concluded that there are a number of significant challenges facing the adjustment of the farm sector towards a more entrepreneurial model of business development arising from the sector's legacy of separation and exceptionalism within the support framework. In order to help encourage the development of generic business skills an ‘intermediary’ model of business advice is advocated, in which an intermediary agency acts as a bridge between farms and generic business support providers.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".