Introduction Environmentally Induced Displacement and Forced Migration
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
Disappearing coastlines, fields and homes flooded by rising waters, lands left cracked and barren by desertification, a snowpack shrinking in circumpolar regions year by year—these are only a few of the iconic images of climate change that have evoked discussion, debate, and consternation within communities both global and local. Equally alarming has been the threat of what such degraded and destroyed landscapes might mean for those who depend upon them for their livelihoods—as their homes, as their means of sustenance, and as an integral part of their cultural and social lives. A mass of humanity on the move—some suggest 50 million, 150 million, perhaps even a billion people1—the spectre of those forced to flee not as the result of war or conflict but rather a changed environment haunts the imaginaries of national governments, international institutions, and public discourse alike. Are these environmental refugees? Should they be granted the same protections and support as those who can prove their fear of and flight from persecution? Do the sheer numbers contemplated by the scale of the events and factors threaten to overwhelm the international refugee system?
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 | 0.000 |
| 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