A protocol for eliciting nonmaterial values through a cultural ecosystem services frame
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Stakeholders' nonmaterial desires, needs, and values often critically influence the success of conservation projects. These considerations are challenging to articulate and characterize, resulting in their limited uptake in management and policy. We devised an interview protocol designed to enhance understanding of cultural ecosystem services (CES). The protocol begins with discussion of ecosystem-related activities (e.g., recreation, hunting) and management and then addresses CES, prompting for values encompassing concepts identified in the Millennium Ecosystem Assessment (2005) and explored in other CES research. We piloted the protocol in Hawaii and British Columbia. In each location, we interviewed 30 individuals from diverse backgrounds. We analyzed results from the 2 locations to determine the effectiveness of the interview protocol in elucidating nonmaterial values. The qualitative and spatial components of the protocol helped characterize cultural, social, and ethical values associated with ecosystems in multiple ways. Maps and situational, or vignette-like, questions helped respondents articulate difficult-to-discuss values. Open-ended prompts allowed respondents to express a diversity of ecosystem-related values and proved sufficiently flexible for interviewees to communicate values for which the protocol did not explicitly probe. Finally, the results suggest that certain values, those mentioned frequently throughout the interview, are particularly salient for particular populations. The protocol can provide efficient, contextual, and place-based data on the importance of particular ecosystem attributes for human well-being. Qualitative data are complementary to quantitative and spatial assessments in the comprehensive representation of people's values pertaining to ecosystems, and this protocol may assist in incorporating values frequently overlooked in decision making processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it