Book and Software Reviews / Critiques de livres et de logiciels
Bibliographic record
Abstract
This excellent book presents an account of second language fluency from multiple perspectives, with a clear focus on cognitive science. Chapter 1 charts the territory. After definitional concerns, broad theoretical viewpoints are presented, such as Levelt’s model of first language speaking and dynamic systems theory. Chapter 2 provides a review of much recent second language research on fluency, with a focus on measurement issues. Chapter 3 reviews general cognitive fluency, exploring areas such as fluency heuristics, transfer-appropriate processing, and processing flexibility. Chapter 4 then explores cognitive aspects of second language fluency. There is a discussion of automaticity and its different underpinnings (ballistic vs. speeded-up processing). The focus is on attentional factors and the use of the Coefficient of Variation as a measure of processing stability. Chapter 5 is concerned with social, attitudinal, and motivation factors. Segalowitz wants to highlight the ways in which language is embedded in social context and their impact on fluency and the attitudes that second language (L2) speakers have toward fluency.
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.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.016 |
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".