Assessing Demographics, Sense of Belonging, and Public Support of PNW Public Land Managers
Faculty mentor/Supervisor:
Claire Rapp
Email Address:
Department Affiliation:
Forest Ecosystems & Society
Project Location:
Corvalis, OR
Project Description:
The project team has a dataset from a recent survey issued to public land managers. The survey includes demographic information for each respondent, as well as measures for respondent's sense of belonging in their job and how much support (or hostility) they feel from the public when trying to make land management decisions. The questions are part of a larger survey examining how public land managers use long-term ecological research to inform their decision-making. We are interested in exploring how sense of belonging and perceived public support may be affected by respondent characteristics. For example, questions worth examining include are certain regions of the PNW categorized by lower public support? Are junior employees or employees from underrepresented social groups more likely to have a lower sense of belonging than senior employees or employees from hegemonic identity groups? We are seeking an undergraduate student to formulate research questions based on the existing data set, conduct analysis, and prepare and write up results for a peer-reviewed publication, most likely a research note for an outlet such as Journal of Forestry.
Describe the type of work and tasks you anticipate the student will perform:
The student will perform typical tasks of quantitative environmental social science, including light data cleaning and preparation, statistical analysis, and writing. The student will work with the project supervisor to identify research questions, hypotheses, and appropriate analysis techniques. Though the exact statistical analysis will depend on the research question the student pursues, we expect the student will likely perform t-tests, chi-squared tests, ANOVA, regression analysis, or similar statistical techniques, preferably in R. The student will be responsible for necessary data visualization, including producing tables and graphs of results. We encourage, though do not require, the student to present their findings at venues such as the Spring Poster Symposium.
Please list special or preferred skills::
Familiarity with introductory statistics (descriptive statistics, difference of means tests, etc.) is required. Experience and familiarity with a stats program of the student's choice (e.g., R, SPSS) is preferred.
Strong writing skills are required.
An interest in environmental social science, such as environmental policy, human dimensions of public lands management, or environmental psychology is preferred.
Certification for Human Subjects Research is required before the student can access the dataset. While students are not required to be certified at time of application, students are encouraged to go through CITI training and earn certification before their start date.
Hourly rate of pay:
$15.00
What is the expected timeline of this project?:
We anticipate the project will take 10 weeks to complete, with the student working 5 hours a week, for a total of 50 hours. Start times are flexible and our timeline assumes the student does not work Thanksgiving week, finals weeks or academic breaks. We anticipate a start date of November 13th, 2023 and an end date of February 23rd, 2024 or until funds are exhausted.
Each week, we expect the student to meet with the project supervisor, Claire Rapp, for at least 1 hour to ask questions, review progress, and assess next steps. Meetings will be in-person or if needed, remote. The student may need to meet for more time some weeks depending on their needs and working style.
We expect each week the student to dedicate the remaining 4 hours a week to working through the steps of the research process. The student will define research questions, propose statistical analyses to address those research questions, conduct the analysis, and write up results for a peer-reviewed publication.
Are special skills or knowledge required to work on this project?:
Yes
Will training be provided?:
Yes
How many hours per week do you anticipate a student to work?:
5 hours per week for 10 weeks.
How many hours per week do you anticipate engaging in direct mentorship?:
At minimum one hour per week, up to 3 hours per week depending on the student's needs.
Detail your mentorship plan:
Claire Rapp will be the supervisor of the undergraduate student and provide mentorship. Mentorship will include, but is not limited to, guiding the student through the research process, helping the student design an analysis plan, answering questions about the project as needed, and providing resources for the student to write their code and conduct analysis. If the student wants to continue to work on the project after funds have exhausted, or if the student proposes additional analysis with the dataset outside the scope of this project, the supervisor will continue to provide mentorship and guidance. Mentorship will also include advice on the student's professional development as they see fit to pursue and providing the student with networking opportunities.