Investigating the Differences Between Prepared and Spontaneous Speech Characteristics: Descriptive Approach
Bibliographic record
Abstract
In the modern EFL paradigm, pre-task planning time is viewed as a norm. Pre-task planning time is one of the central concerns of teachers, test-developers, as well as researchers. Pre-task planning is planning a speech before performing a task, and it also involves rehearsal and strategic planning. The paper addresses the problem of pre-task planning advisability for A2 Russian EFL speakers. The research presented in this paper examines the structure, breakdown, repair, syntactic complexity, lexical diversity as well as the accuracy of the discourse produced by 145 Russian participants of the English language competition held in Kazan, Russia, in January 2020. The discourse analysis revealed that the pre-task time is used by A2 EFL speakers not only to focus on a dialog but also to elicit a topic text from memory, thus focusing on form rather than meaning. Hence, in A2 tests prioritizing meaning over form and measuring the ability for spontaneous speech, the one-minute pre-task planning time is viewed as questionable.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".