Divergent values and perspectives drive three distinct viewpoints on grizzly bear reintroduction in Washington, USA
Data files
Nov 08, 2024 version files 138.59 KB
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Raw_Sorts_for_Dryad.xlsx
130.29 KB
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README.md
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Statements_for_Dryad.csv
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Abstract
The success or failure of apex carnivore reintroduction efforts can hinge on understanding and attending to diverse viewpoints of those involved in and impacted by reintroductions. Yet, viewpoints vary widely due to a suite of complex and intersecting factors, such as values, beliefs, and sociocultural context. We ask, “what are the diverse viewpoints that exist surrounding apex carnivore recovery and what kinds of emotional, analytical, and values-based judgments might people use to construct their viewpoints?”
We used Q-methodology to identify distinct, generalized viewpoints, and areas of overlap and divergence between them, surrounding a proposal to reintroduce grizzly bears (Ursus arctos horribilis) to the North Cascades Ecosystem, USA. Q-methodology combines qualitative and quantitative methods by asking purposefully sampled respondents to sort various statements on a given topic into an ordered grid.
We found three distinct viewpoints among 67 respondents using factor analysis and responses to open-ended questions about the sorting exercise. Two of these viewpoints represent essentially polarized perspectives corresponding to deeply normative notions about grizzly bear recovery, where one views reintroducing bears as a moral requisite, and the other views it as inappropriate and risky. These viewpoints primarily diverged on their perceptions of risk and perspectives about our collective responsibilities to and appropriate relationships with others (i.e., “relational values”). The third viewpoint was distinguished by its prioritization of practical considerations and views reintroducing bears as impractical and not sensible.
Our analysis underscores the need to identify and attend to latent viewpoints that may be overlooked in the polarized public discourse as well as the multiple value systems and perceptions of risk that are integrated in perspectives on grizzly bear reintroduction. Additionally, our broadly defined identity groups were of very little utility in predicting viewpoints in this study, highlighting the importance of avoiding assumptions about people’s views based on their identities and interests.
We argue that forefronting conversations about responsibilities and appropriate relationships is critical for finding acceptable paths forward in such recovery efforts. We discuss the management implications of these findings for the North Cascades grizzly bear reintroduction and for other large carnivore reintroductions.
https://doi.org/10.5061/dryad.73n5tb369
Description of the data and file structure
This dataset contains answers to a short questionnaire and the Q-sort rankings each participant gave to 41 statements depending on how much they agreed or disagreed with each statement. The scale of agreement ranges from -5 (strongly disagree) to +5 (strongly agree), and participants were “forced” to prioritize statements by sorting them in a grid (see figure in supporting information) which only allowed for one statement to be ranked -5 and one statement ranked +5. Several statements could be ranked neutrally (0).
Files and variables
File: Statements_for_Dryad.csv
Description: These are the statements that were ranked by participants in the Q-sort grid and their corresponding ID number (s1, s2, …).
Variables
- ID: Statement id that corresponds to the raw sorts header row.
- Statement: Text of each statement that participants sorted in the Q-sort activity.
File: Raw_Sorts_for_Dryad.xlsx
Description: This contains the answers to the preliminary questionnaire participants answered that collected basic demographic and familiarity information. It also contains how each participant ranked each statement (-5 to +5) based on level of agreement with that statement.
Blank cells (unanswered questions) are filled in with “N/A”.
Variables
- Number: The numerical id of each participant. Corresponds to Figure 2 in the manuscript.
- Participant: Participant identifier given by the software.
- Loading: The factor which each participant loaded onto in our analysis.
- Year_born: Year the participant was born.
- Gender_identity: Self-identified gender of the participant.
- Primary_role: The role which the participant identified with most strongly as it pertains to their activities or involvement in the North Cascades Ecosystem (See manuscript and supporting information for questionnaire details).
- Secondary_role1 through Secondary_role3: Participants had the option to select up to 3 additional roles they identify with. Some selected their primary roles twice.
- DEIS_familiarity: The level of familiarity participants had with the 2017 Draft Environmental Impact Statement, with 4 categories of familiarity.
- s1 through s41: The ranking given to each statement by each participant.
Code/software
Our analyses were performed in Q Method Software, which is a paid subscription service: https://qmethodsoftware.com/
However, analysis is possible using the open software KenQ: https://shawnbanasick.github.io/ken-q-analysis/ The website provides substantial instructions for use of their software, and has the same options for analysis which are:
- We generated a Pearson correlation matrix of every Q sort.
- We used the matrices to conduct a centroid factor analysis.
- We used a combination of judgmental hand rotation and Varimax rotation to explore Q sort loadings relative to two, three, and four extracted factors.