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
The US is the country of immigration, with almost 20 per cent of the world’s 260 million international migrants. The number two country with international migrants, Germany, has 12 million, a fourth as many as the almost 48 million foreign-born US residents (UN DESA, 2017). The US stands alone among industrial countries in having a quarter of its immigrants, almost 11 million, unauthorised (Passel and Cohn, 2018). President Trump made reducing illegal immigration a priority. Major migration issues today include the fate of programs such as DACA, what to do about Central American families who apply for asylum, and whether to build a wall on the Mexico-US border. In December 2018-January 2019, there was a partial shutdown of the federal government, the third in Trump’s first two years as President, because Congress failed to include $5 billion for the border wall in bills that fund DHS and other federal agencies. Meanwhile, Mexico agreed to issue humanitarian visas to Central Americans who enter the US and apply for asylum, so that Central American asylum seekers may wait in Mexico for US decisions on their cases
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