Does psychic numbing apply to endangered species conservation? The case of the Peregrine Falcon in Berkeley, California
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
Introduction Many individuals exhibit compassion towards charismatic animals in distress, yet they are not as motivated to help the thousands of endangered animal species. The foundation of this paradox is psychic numbing, a psychological phenomenon that explains why people are more inclined to donate to help save human lives when presented with accounts of single identifiable victims compared to accounts of mass atrocities like genocide. The impact of psychic numbing on human tragedies has been well documented, but its impact on non-human tragedies, such as the crisis of endangered species conservation, has not been thoroughly assessed. Methods This study uses Peregrine Falcon ( Falco peregrinus ) conservation as a case study, examining whether identifiable lives or statistical lives elicit the greatest concern for Peregrine Falcon preservation and increased donations. Participants are randomly presented with one of three messages: (1) The story of Annie, a celebrity falcon residing in the University of California, Berkeley, (2) Statistical data on Peregrine Falcon decline and history, or (3) A combination of Annie’s story and statistical data. Results We did not find a significant difference in donation amount for identifiable versus statistical lives. However, the three different messaging conditions did evoke significant differences in word association tasks about endangered species. Discussion Our results demonstrate the importance of further research into messaging conditions that will bring about the greatest level of human action for endangered species conservation.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it