The Consequences of English Learner as a Category in Teaching, Learning, and Research
Bibliographic record
Abstract
Abstract The evolution of a pervasive negative view of immigrants and its role in classroom achievement in the United States is described in this paper; beginning in the crowded urban secondary classrooms of the 1800s, to IQ testing in the 1920s that identified many as morons, imbeciles, or idiots, and to an English‐only view that permeates public and political views of teaching and learning. It is argued that categories such as ELL are ill‐advised because they obscure diversity and inform neither instruction nor research because they are unidimensional and misrepresent important underlying diversity. It is argued that evidence‐based strategies should inform teaching and learning, but that evaluating research is the purview of teachers themselves, including conducting classroom‐based action research to test recommended strategies. Concludes with general guidelines to evaluate research.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.027 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".