Editing Academic Books in the Humanities and Social Sciences: Maximizing Impact for Effort
Bibliographic record
Abstract
This article explores the difficulties commonly experienced by academics seeking to edit multi-chapter, multi-contributor edited volumes. Edited volumes play important intellectual and community-building roles in the Humanities and Social Sciences (HSS) sector. Yet these significant positive contributions are not always apparent to or valued by tenure and promotion committees. The article identifies several key problems editors face in the formulation and execution of their volumes. It aims to assist prospective editors in ensuring that the time spent editing or co-editing a book remains proportional to the likely return for effort. The article concludes with the argument that the recent emergence of Google Scholar Citations will enable HSS-sector academics to break free of the hegemony of the science-based model for quality assurance that privileges Institute for Scientific Information (ISI) journal articles and will reveal the considerable impact of edited volumes and therefore increase their value as markers of quality scholarship.
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 | 0.195 | 0.095 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.030 | 0.030 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.127 | 0.102 |
| Open science | 0.004 | 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".