Abstraction and the (Misnamed) Language Familiarity Effect
Bibliographic record
Abstract
Talkers are recognized more accurately if they are speaking the listeners' native language rather than an unfamiliar language. This "language familiarity effect" has been shown not to depend upon comprehension and must instead involve language sound patterns. We further examine the level of sound-pattern processing involved, by comparing talker recognition in foreign languages versus two varieties of English, by (a) English speakers of one variety, (b) English speakers of the other variety, and (c) non-native listeners (more familiar with one of the varieties). All listener groups performed better with native than foreign speech, but no effect of language variety appeared: Native listeners discriminated talkers equally well in each, with the native variety never outdoing the other variety, and non-native listeners discriminated talkers equally poorly in each, irrespective of the variety's familiarity. The results suggest that this talker recognition effect rests not on simple familiarity, but on an abstract level of phonological processing.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".