Listening for the Ivory-billed Woodpecker: Sonic geography and the making of extinction knowledge
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
If an apparently extinct bird calls in a forest, and there are people there to hear it-to record it, even-is it still extinct? The Ivory-billed Woodpecker was last 'officially' seen in the United States in 1944, but its extinction continues to be a subject of intense debate between conservation authorities, scientists, and grassroots activists. Tensions peaked around 2005, when scientists from the Cornell Laboratory of Ornithology announced their rediscovery of the species. However, their evidence received significant challenge from other ornithologists, and this apparent rediscovery has since been generally dismissed. In 2021, the United States Fish and Wildlife Service recommended the ivorybill be declared officially extinct. Still, many people continue to trawl the Southeastern forests in search of ivorybills. In this article, I investigate the methods, debates, and results of efforts to locate this species, with a focus on sound. In doing so, I explore the interconnected roles of sound and space in the making of extinction knowledge. Sonic search methods of listening, sounding, and translating are core ways that searchers attempt to attune to, communicate with, and establish evidence of ivorybills. Additionally, sonic search practices are critical spaces of negotiation and contestation between different searchers, between searchers and ivorybills, and between searchers and skeptics. Ultimately, this article argues that sonic geographies affect the production of extinction knowledge, and vice versa-extinction knowledge making practices produce distinct sonic geographies.
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 | 0.001 | 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 | 0.001 | 0.004 |
| 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