Commentary. Integrating Research, Education, and Traditional Knowledge in Ecology: a Case Study of Biocomplexity in Arctic Ecosystems
Bibliographic record
Abstract
Integrating research and education is a fundamental goal of institutions and agencies supporting science because of the benefits to society of a more informed and scientifically literate population. The value of engaging public interest in ecological research is to maintain support for and integrate science in solutions to environmental problems (Hudson, 2001; Avila, 2003). The National Science Foundation lists criteria for assessing broader impacts of research projects which include (1) the integration of research and education—advancing discovery and understanding while promoting teaching, training, and learning; and (2) developing opportunities to broaden the participation of groups underrepresented in science (NSF, 2006). Educational researchers are developing models and assessing outcomes of integrating research and education at diverse grade levels (Trautmann and Krasny, 2006; Bowen and Roth, 2007); the value of integrating traditional ecological knowledge (TEK) in research has been demonstrated in several ecosystems (Huntington, 2000; Kimmerer, 2002; Ford et al., 2007; Garcia-Quijano, 2007) but specific approaches and achievements of efforts integrating research and education are not widely disseminated in environmental research journals. Thus, while there is a call for environmental scientists to broaden their activities to engage in outreach (i.e., have broader impact) there is a lag in the assessment of the effectiveness of these activities and of their value in mainstream scientific culture. Environmental scientists seldom evaluate these impacts, and there are few venues or incentives to report on these activities in ways that would enhance their research careers. For an individual scientist, efforts expended in integrating research and education often occur at the expense of research productivity and this results in a lack of reward for a researcher’s efforts to broaden research impacts (Andrews et al., 2005; Uriarte et al., 2007). One way to address the imbalance between efforts devoted to broader impacts vs. avenues for reporting on these efforts is through the publication of case studies and assessments of integration efforts in journals that reach a research audience as opposed to an education audience. This venue exists in a very few, high-profile, broad-interest research journals (e.g., Science, Bioscience) but could be more widespread in journals addressing a range of environmental research. Examples of successful integration help researchers and institutions evolve better mechanisms to achieve goals beneficial to society, including improved public understanding of science, greater diversity of research and stakeholders, and better application of current scientifically based information to managing environmental issues. In that spirit, we present as an example an effort integrating an interdisciplinary research project investigating the interactions of climate, vegetation, and permafrost in the study Biocomplexity of Arctic Tundra Ecosystems with a university field course, Arctic Field Ecology, and with indigenous Inuit students and elders. The integration allowed university students and native community members to participate with the research team, drawn by the opportunity to gain education and experience. This participation has had synergistic benefits with the research agenda and diversified the pool of stakeholders involved in the research (see Box 1).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".