@article {3672,
	title = {Body condition scoring of sheep: intra- and inter-observer variability},
	journal = {New Zealand Journal of Animal Science and Production},
	volume = {80},
	year = {2020},
	month = {09/2020},
	pages = {107-112},
	address = {Online},
	abstract = {Body condition scoring (BCS) is a hands-on tool that farmers can use to make decisions about their animal feeding and management.
BCS, however, is a subjective measure of the muscle and fat cover of the lumbar spine. Observers, therefore, may show variability
in scores both across time and from other observers. This study aimed to determine the intra- and inter-observer variation of both
farmers and research technicians as part of a learning exercise of a farmer-learning group based at Massey University between
2011 and 2015. Nineteen farmers and three research technicians condition scored 45 mixed-age ewes on two consecutive days.
Data from both farmers and technicians were analysed to determine the intra- and inter-observer variability using a weighted
kappa. The results indicate that the majority of farmers and technicians had {\textquoteleft}excellent{\textquoteright} agreement (21 of the 22 observers had
kappa values greater than 0.75) between days. Similarly, among pairs of observers the agreement was also {\textquoteleft}excellent{\textquoteright} (212 of
231 comparisons had kappa values greater than 0.75). The distribution of scores that contributed to each median condition score,
however, indicated that lower scores (1, 1.5 and 2) has less variability than did higher scores (2.5 or greater). These results suggest
that BCS is a robust farm-management tool that can be used with a high degree of repeatability.
Keywords: body condition scoring; intra-observer variability, inter-observer variability},
	issn = {1176-5283},
	author = {Corner-Thomas RA and Sewell AM and Kemp P and Wood BA and Gray DI and Morris ST and Blair HT and Kenyon PR}
}
@conference {3678,
	title = {The Farmer Learning Project: Improving the design of agricultural extension to promote learning},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {74},
	year = {2014},
	month = {06/2014},
	pages = {166-172},
	address = {Napier},
	abstract = {New Zealand has played a key role in developing innovative extension models designed to support farmers to adopt new, evidence-based, farming practices. However, this momentum has been lost over recent years. A fresh and innovative model of extension is needed to ensure that New Zealand farmers learn about highly-effective technologies. The Farmer Learning Project, now in its third year, is a multi-disciplinary research venture that aims to find out how to promote farmers{\textquoteright} learning and adoption of evidence-based practices. This paper provides an overview of the Farmer Learning Project at Massey University and its innovations designed to promote learning about herb-mix pastures containing chicory, plantain and red and white clover. Five critical success factors shown to support the farmers{\textquoteright} learning are discussed. These include the importance of participation in a sustained and inquiry-focused farmer-scientist learning community, and their engagement in a variety of repeated and relevant learning experiences that are aligned to science. Underpinning these success factors are seven educational principles that need to inform design innovations in agricultural extension. Early findings are also shared from the second phase of the project, which investigates the farmers{\textquoteright} practice change as a result of their learning about herb pastures and its ability to create high performance sheep grazing systems.},
	issn = {1176-5283},
	author = {Sewell AM and Blair HT and Grey DI and Hartnett M and Kemp PD and Kenyon PR and Morris ST and Wood BA}
}
@conference {3678,
	title = {From Extension to Distributed Learning: The Embedding of Agricultural Scientists in Farmer Knowledge Networks},
	booktitle = {Proceedings of the New Zealand Society of Animal Production},
	volume = {74},
	year = {2014},
	month = {06/2014},
	pages = {173-178},
	address = {Napier},
	abstract = {This paper reports on the social structures of an ongoing learning group in which 17 farmers and five agricultural scientists are collaboratively undertaking a three-year farmlet experiment that investigates the performance of {\textquoteleft}herb mix{\textquoteright} pastures. Network analyses have been undertaken of the history of prior contact between the group{\textquoteright}s 22 members and of the 223 contacts made by the participating farmers to develop their herb pasture knowledge. The results show that networking by farmer members radically increases the ability of science to reach other farmers. These farmer networks have distributed structures characterised by dense, decentralised and equitable ties between the participants. The power to authorise agricultural knowledge is pluralised by numerous self-reinforcing relationships grounded in everyday farming practices. The paper concludes by discussing the relevance of such distributed learning for current attempts to replace linear extension with a more productive approach to agricultural knowledge.},
	issn = {1176-5283},
	author = {Wood BA and Blair HT and Grey DI and Hartnett M and Kemp PD and Kenyon PR and Morris ST and Sewell AM}
}
