Shallow semantic processing of text: Evidence from eye movements
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
Evidence for shallow semantic processing has depended on paradigms that required readers to explicitly report whether they noticed an anomalous noun phrase (NP) after reading text such as ‘Amanda was bouncing all over because she had taken too many tranquillizing sedatives in one day’. We replicated previous research by showing that readers frequently fail to report the anomaly, and that less-skilled readers have particular difficulty reporting locally anomalous NPs such as tranquillizing stimulants. In addition, we examined the time course of anomaly detection by monitoring readers’ eye movements for spontaneous disruptions when encountering the anomalous NPs. The eye fixation data provided evidence for on-line detection of anomalies; however, the detection was delayed. Readers who later reported the anomaly did not spend longer processing the anomalous NP when first encountering it; however, they did spend longer refixating it. Our results challenge orthodox models of comprehension that assume that semantic analysis is exhaustive and complete.
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