Christopher S BovaOne Ocean Hub · Blue Economy and Society
Christopher S Bova
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Citations since 2016
7 Research Items
Fishing guides are held in high esteem by recreational fishing clients whom they likely influence (for better or worse) through role-modelling. This, coupled with consensus that angler behaviour is a key determinant of ecological outcomes in the catch-and-release (C&R) process suggests exploring the state of fishing guide knowledge, attitudes and b...
Non-compliance with recreational fishery regulations is considered to be one of the biggest threats to the sustainability of fisheries. Dedicated non-compliance studies are seldom carried out at the national level which makes it difficult to discern the behavioural compliance norms within a population. The instrumental approach for compliance is th...
Fishing guides are respected as opinion leaders of the recreational angling community, but little is known of their influence on angler behaviour. Given their social-standing, fishing guides may be perceived as role models by fishing clients – thereby potentially shaping the practices of many through their extensive networks of fishing clients. Thi...
While the economic activity associated with recreational fishing is well assessed in the developed world, substantially less is known in developing countries. South Africa is a unique microcosm for applying economic evaluation frameworks through its dualist economy, which shares characteristics of both the developed and developing world. Understand...
This study aimed to assess the suitability of the Berkowitz' (2005) social norms approach (SNA) for improving compliance behaviour amongst recreational fishers. A total of 138 recreational shore anglers were interviewed in Eastern Cape, South Africa and asked about their compliance, attitudes towards compliance, perceptions of compliance and the at...
If a course instructor at an education center wanted to custom tailor their course material around the socio-cultural perspectives of the visiting class/group, they may send out a pre-course survey to the teacher/group leader that tries to identify those perspectives. However, the typical questions for eliciting demographic information are not well suited for a teacher/group leader to respond to.
How then, might a question be posed to a group leader about the demographic composition of their group?
For instance, group age is quite easy as the question could be posed as "What is the average age of your group"....or......"what is the age range of your group".
The problem lies around trying to understand the racial and cultural identifications of the group. In the United States, a school classroom may have a diverse range of races and cultures. How can an instructor at an external education center (ie. museum, library) identify the various races and cultures of the group so that their lesson does not only cater to the majority?
I'm looking for specific examples that will not require too much effort on their primary teacher's behalf (no surveying of the classroom).
Say a framework for assigning orientations to data has been developed where these orientations are designated using confirmatory factor analysis (CFA). The a priori assumptions in the CFA are based on a single (potentially context specifc) study which created established the orientation categories.
How do I test whether these orientations, and how they are assumed to relate to the data, are valid in a different context?
I am trying to compare the two multivariate analysis methods but there is little information on the benefits of one over the other. I'm not talking about principle component analysis (PCA).
I have found that, without reference, several articles state that fisheries regulations are derivative of terrestrial resource regulations (hunting, logging). While certain aspects are similar, such as quota systems, permit requirements, closed seasons etc., I have yet to find clarity as to which came first and whether or not one is, in fact, based on the other. It's useful to know if the regulations share a similar foundation as a framework for reducing illegal resource use from one may be applicable to the other.
KEYWORDS: Forestry, Fishery, Recreation, Hunting, Regulation, Non-compliance, Resource, terrestrial, marine, history
I have combed through many studies pertaining to estimates of illegal resource use. The authors rely on responses from survey participants, which are prone to social desirability bias. To control for SDB, they employ the Random Response Technique (RRT). With the help of a randomising device (a coin or die), interviewers offer statistical noise which can help conceal a participants response, thereby increasing anonymity and encouraging the respondent to answer honestly.
Although it seems practical in theory, the same statistical noise that is meant to reduce SDB could result in participants not following instructions due to the perception of forced admissions of sensitive behaviour participation implicating them in something they did not do. Additionally, do participants really comprehend the statistics well enough to understand how their responses are concealed?
The only validations I could find of the RRT were weak comparative studies with a "more is better" assumption, that is more admissions to the sensitive behaviour of interest equates to a more accurate method and a reduction in SDB. However no studies have actually validated the prevalence of these behaviours to any directly observed data.
In fact, many studies in the social sciences have found the RRT to often produce paradoxical estimates, waste a significant amount of data, requires significantly more resources to administer and that the instructions and method are not easily understood by participants.
Yet the RRT is growing in popularity in the literature. My question is, with no strong evidence of its validity, why is RRT so readily employed in the literature?
In this project we aim to strengthen our knowledge of the environmental attitudes and perceptions, understand the social norms, and test a variety of normative interventions to improve compliance in South Africa’s marine recreational fisheries. By improving compliance in the fisheries sector with the largest participation rate, this project will contribute significantly to the development of the small-scale and subsistence fisheries, which is part of the government’s long-term plans for improving the livelihoods of coastal communities.