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      Fellow cows and conflicting farmers: Public perceptions of dairy farming uncovered through frame analysis

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          Abstract

          Divergence in opinion over how farm animals should be cared for is creating a disconnect between livestock farming and the public that risks a loss of “social license” to farm. One proposed solution for the dairy farming community is to engage more constructively with the public to develop a shared vision of the industry's future; however, farmers and veterinarians remain reluctant to validate public opinions on farm animal care, in particular, often viewing them as naïve or impractical. Understanding the interpretive frames through which people make sense of dairy farming could help the dairy farming community engage more constructively with public opinion, thereby reducing conflict and providing opportunities to change communication or practice. Hence, frame analysis was conducted on transcripts of 60 face-to-face interviews with members of the UK public, first defining frames using reflexive thematic analysis, then considering the effect of these frames on those holding them. The results showed that dairy farming was mainly characterized by two entities: the cow and the farmer. Three frames were developed for the cow: she was perceived as i) enduring, which induced a sense of moral responsibility for her well-being among participants; ii) a fellow or companion, which led to feelings of a shared or parallel life with her; and iii) a force of nature, where the cow's connection with the natural world and “otherness” was appreciated, or even longed for. These connections were unexpectedly widespread within the sample, with many participants simultaneously holding two or even three frames. The farmer was seen through two frames: i) traditional; or ii) modernizing, but both frames had positive and negative narratives depending on the perceived care of the cow, causing confusion or even conflict about the care the farmer actually delivered. These findings provide new insights into the interpretive lenses through which the public makes sense of the dairy cow and her care, not least the bond the public themselves feel with the animal. They offer fresh opportunities for the dairy industry to improve engagement through more reflexive communication or modification of farming practices to better fit societal expectations about dairy cow welfare.

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          Sample Size in Qualitative Interview Studies: Guided by Information Power

          Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is "saturation." Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose the concept "information power" to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power depends on (a) the aim of the study, (b) sample specificity, (c) use of established theory, (d) quality of dialogue, and (e) analysis strategy. We present a model where these elements of information and their relevant dimensions are related to information power. Application of this model in the planning and during data collection of a qualitative study is discussed.
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            Judgment under Uncertainty: Heuristics and Biases.

            This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.
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              Comparison of Convenience Sampling and Purposive Sampling

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                Author and article information

                Contributors
                Journal
                Front Vet Sci
                Front Vet Sci
                Front. Vet. Sci.
                Frontiers in Veterinary Science
                Frontiers Media S.A.
                2297-1769
                17 November 2022
                2022
                : 9
                : 995240
                Affiliations
                Ruminant Population Health, The School of Veterinary Medicine and Science, University of Nottingham , Nottingham, United Kingdom
                Author notes

                Edited by: Orla Shortall, The James Hutton Institute, United Kingdom

                Reviewed by: Philip A. Robinson, Harper Adams University, United Kingdom; Mette Vaarst, Aarhus University, Denmark; Mari Nicholls Espetvedt, Vestfold and Telemark County Council, Norway

                *Correspondence: Jasmeet Kaler jasmeet.kaler@ 123456nottingham.ac.uk

                This article was submitted to Veterinary Humanities and Social Sciences, a section of the journal Frontiers in Veterinary Science

                Article
                10.3389/fvets.2022.995240
                9714478
                36467655
                ccd297dd-6719-417f-88dd-78f094cc5e9b
                Copyright © 2022 Jackson, Green and Kaler.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 15 July 2022
                : 03 October 2022
                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 114, Pages: 18, Words: 14596
                Funding
                Funded by: Agriculture and Horticulture Development Board, doi 10.13039/100008123;
                Categories
                Veterinary Science
                Original Research

                frame analysis,animal welfare,dairy cow,dairy farmer,reflexive thematic analysis

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