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
This paper critically examines Tomlin and Villa's (1994) fine-grained analysis of attention and Leow's (1998) attempt to operationalize their model. Our position is that whereas Tomlin and Villa have moved the attention research forward by describing the nature of attentional processes and by pointing out that detection is a critical function of SLA, their claim that alertness and orientation are not necessary for detection to occur is currently unsupportable and does not reflect the complex nature of SLA. We argue that Leow's efforts to provide empirical support for this model fall short of that goal. Additionally, we cast doubt on Tomlin and Villa's position that awareness is not required for the detection of L2 data by arguing that the issue of awareness as well as the role of attentional functions must be viewed from a more interactive perspective in terms of the nature of the task, the nature of the linguistic item, and individual learner differences. We conclude by proposing research orientations that may help advance the discussion on this topic.
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