A Bibliometric Analysis of Book Reviews Published in Translation Journals between 2010 and 2021
Bibliographic record
Abstract
Contrary to the emphasis placed on the importance of book reviews as influential drivers of intellectual exchange in the social sciences and humanities, there is a lack of attention by researchers toward the potential of this academic form as a valuable research material and data source. This study aims to bridge this research gap by conducting a bibliometric analysis of 1814 book reviews published in fourteen reputable translation journals during the 2010–21 period. Four major findings were outlined: a slight decline in the number of book reviews in the translation discipline, a propensity among translation journals to favour highly organized yet somewhat mundane book reviews, an evident geographical concentration of contributors toward book reviewing, and prestige and topic biases involved in the proliferation of multiple reviews for a book.
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 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 | 0.020 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.163 | 0.276 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.019 | 0.083 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".