Staging an Experience of Cultural Heritage Preservation: Consumers' Willingness to Pay for Heirloom Rice in the Philippines
Bibliographic record
Abstract
ABSTRACT The Cordillera Administrative Region in the Philippines is home to terraced rice embedded in centuries of cultural heritage. However, weak market incentives threaten sustained production, jeopardizing indigenous communities' cultural heritage and the in situ biodiversity of rice genetic resources. Demand‐side policy interventions have been proposed to address these challenges. Drawing on the experience economy, we staged an experience with urban consumers, offering them the opportunity to participate in cultural heritage preservation through purchasing heirloom rice. Participants first self‐selected into white or brown rice market segments as a benchmark. Subsequently, each market segment was invited to (i) identify their preference between their benchmark and heirloom rice, and (ii) bid to upgrade their non‐preferred to their preferred rice through a Becker‐DeGroot‐Marschak (BDM) mechanism. The sample was randomly split between a control group and two “experience treatment” groups exposed to gain‐ or loss‐framed narratives about rice terrace preservation. Results reveal that a subset of consumers in each market segment switched to heirloom rice. White rice consumers were more reluctant to transition to heirloom rice, although they responded positively to the gain‐framed narrative, paying the highest price premiums for heirloom rice (PhP 92.55 or US $2.03 per kilogram). Brown rice consumers were more willing to switch but willing to pay lower premiums for heirloom rice, altogether suggesting the need for a segmented marketing strategy. Highlighting nutritional benefits and quality is crucial, but positioning heirloom rice within a gastronomic system that showcases its use in specific dishes and occasions is equally important for enhancing consumer appeal.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".