Bibliographic record
Abstract
To determine how accurately adult listeners can identify speaker sex in children's voices, we presented vowels in /hVd/ syllables produced in isolation and in a brief carrier sentence by five boys and five girls from each of four age groups (5–8, 9–12, 13–16, and 17–18 yr). Speaker sex identification improved with increasing age of the speaker, but even in the youngest group performance was significantly above chance. Strong biases were noted, with older boys more accurately classified than older girls, while the reverse pattern was found at younger ages. Listeners sometimes reported difficulty distinguishing the older girls from younger pre-adolescent boys. Recognition of speaker sex from isolated syllables was more accurate and listeners were more confident of their responses when informed of the age of the speaker. Performance was also higher when syllables were embedded in a carrier phrase, and in this condition the advantage provided by knowledge of the speaker's age was reduced. The results indicate that the perception of speaker sex can be informed by knowledge of the speaker's age, and that sentence context provides additional cues to speaker sex in children's speech.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".