Dissemination of Research Findings
Bibliographic record
Abstract
Designed for graduate students, instructors, and seasoned researchers, this is an essential guide for robust research design and methodology in applied linguistics, covering qualitative, quantitative, and mixed methods research. It adopts a structured approach, starting with the foundational principles of research design, methodology, and data collection and analysis, to writing and interpreting, explaining, and reporting research results, bringing together all the steps and processes of research from start to finish in one single volume in a way that is practical, easy to follow, and easy to understand. Throughout, the emphasis is on the process of research and the application of various research techniques and principles across different areas. These characteristics, coupled with numerous pedagogical features such as key term reviews, visuals, research scenarios, and many discussion and activity questions, make the book an indispensable reference and a valuable textbook for courses in second language and applied linguistics research.
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 | 0.121 | 0.323 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.092 | 0.083 |
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".