The increasing diversity of rural landholders and inconsistent framework utilized to classify and compare the range of landholders is problematic. A myriad of items are often selected to separate landholders into similar categories. Occupational identity is one item receiving greater attention in the literature as a variable that is able to separate landholders without the reliance on items related to land use or income - two items that are heavily relied upon, but that change greatly from one context to another making a direct comparison between landholders across contexts difficult. This research utilizes the Collective Identity Construct, a multidimensional socio-psychological measure, to test the utility and applicability of a farmer occupational collective identity to classify rural landholders. A mixed methods approach is utilized in a comparative study between landholders in Ohio, USA and Victoria, AU. This research explores the extent that the seven Collective Identity Construct dimensions are applicable across different economy contexts and geographical locations. Data analysis indicates that six of the seven Collective Identity Construct dimensions are useful in forming a valid and reliable scale to measure a farmer occupational identity. This new measure is called the Collective Occupational Identity Construct (COIC) and is able to distinguish between three broad landholder cohorts (full-time farmer, part-time farmer, non-farmer), but with a more nuanced approach and outcome of landholder separation. COIC is utilized to create a landholder typology and profile of four types of landholders in North Central Victoria, and an exploration of the relationship between COIC and land management practices identifies the strength of this dimension in predicting landholder behavior. Natural resource management implications are provided to guide future policy and program implementation.
|Qualification||Doctor of Philosophy|
|Award date||26 Aug 2015|
|Place of Publication||Australia|
|Publication status||Published - 2016|