A Per-second Investigation of the Interconnectedness between Linguistic and Cognitive Factors Underlying L2 Willingness to Communicate
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
Willingness to communicate (WTC) research has recently witnessed a paradigm shift with the more recent studies looking at the shifting and dynamic nature of the variable. A growing body of literature has interpreted such dynamicity from a complex dynamic systems (CDS) perspective. The theory of CDS has four basic properties, one of which, and the focus of this study, is the interconnectedness among subsystems. This property mainly involves the interplay amongst parts of a system, which interact and influence one another, determining the subsequent dynamics in the system. This qualitative, exploratory study employed an idiodynamic method to investigate the interconnectedness of the cognitive and linguistic factors underlying second language (L2) WTC. To this end, 20 participants completed four three-minute monologic speaking tasks while being video-recorded. Immediately after, they viewed their recordings, rated their WTC moment by moment, and explained the WTC changes in stimulated recall interviews. The interviews were coded, and instances where WTC was affected by cognitive and linguistic factors were identified and analysed. Three patterns of interconnectedness emerged: (1) WTC and linguistic factors; (2) WTC and cognitive factors; and (3) WTC, and linguistic and cognitive factors. Findings provide a clearer account of the interconnectedness property in the WTC system, lending support to viewing WTC as a CDS. The article highlights the importance of self-perception and availability of content message, in addition to the above factors, and concludes with a brief discussion of the pedagogical implications for L2 classroom.
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 | 0.001 | 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 | 0.002 | 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