Trends of replication studies in Applied Linguistics journals: A systematic review over half a century
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
Despite the importance of replication research in scientific fields, very few replications are conducted in applied linguistics (AL). To enhance language researchers’ awareness of replications and provide a systematic evaluation of current replications, this study analyzed replication studies published in 92 AL leading journals from 1970 to 2021 based on five themes of replication labels, methodological orientations, research trends, authorship, and citation counts of replicators. The results reveal that replication labels have explicitly been mentioned since 2002, the replication of quantitative studies has predominately been raised, studies on second language acquisition were frequently replicated, collaborative authorship has increased in replications, and influential AL scholars tend to conduct replication research. The study highlights the need for a well-established replication classification and calls for replication research in the areas and methodological orientations marginalized in AL. It is also recommended that prominent figures perform more replication research to consolidate its status in AL.
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 | 0.007 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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