Robust inference processes in expository text comprehension
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
Abstract Expository text offers particular challenges to the reader because of the abstract and unfamiliar concepts that it presents and its distinctive structure. The present study had three interrelated aims: (1) It examined the impact of appropriate connectives on the reader's derivation of causal bridging inferences from expository text. (2) It scrutinised texts longer than the ones that we had previously examined (Singer, Harkness, & Stewart, 1997), which in turn made it possible to (3) evaluate the impact of position in the text on inference processing. In Experiments 1a and 1b, a joint profile of target reading times and inference answer times indicated that the inspected inferences reliably accompanied reading only in the presence of appropriate causal connectives. The connective-present conditions of Experiment 1 replicated our previous findings using shorter texts (Singer et al., 1997). Experiment 2 indicated that these inference processes are unaffected by text position. We interpreted these findings with reference to the inference validation model (Singer, Halldorson, Lear, & Andrusiak, 1992).
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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