The effects of topic title on language comprehension and working memory resources
Bibliographic record
Abstract
This study was designed to explore the effects of topic title and simulated high frequency hearing loss on language comprehension by normal, healthy adults. Thirty-two adult participants with no history of cognitive deficits participated in this study. Each participant listened to four different passages in four different conditions. The four conditions were: (1) title with normal hearing, (2) title with simulated high frequency hearing loss, (3) no title with normal hearing and (4) no title with simulated high frequency hearing loss. Passages were presented segment-by-segment using the auditory moving window technique; most segments were short sentences or clauses. Participants listened to each segment at their own pace by pressing a key. Pause times between segments and overall listening time were recorded for each passage. After listening to each passage, participants were asked to recall out loud what they understood and remembered from the passage. Recall was transcribed and percentages of recalled propositions were calculated. In order to observe changes in processing across a passage, mean pause duration values were also compared across passage position (beginning, middle and end of a passage). The results showed that topic titles facilitated listening comprehension, as shown through better recall performance and reduced processing time. The knowledge of topic titles also reduced the time required for processing information at the beginning of the passage, showing that the knowledge of topic titles facilitates the building of mental representations. The simulated high frequency hearing loss condition did not prove to consistently tax working memory resources during language comprehension. The findings also provided evidence about the relationship between working memory ability and recall performance. Overall, these findings are consistent with the predictions of current language comprehension models.
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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 | 0.001 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".