Bibliographic record
Abstract
2010 was an excellent year for Family Business Review (FBR), as the journal continued on its positive trajectory on all key metrics.The Impact Factor from the Journal Citation Report rose from 1. 357 in 2009 (and 0.675 in 2008)to 1.881 in 2010, ranking FBR as 26th out of 87 business journals.The e-alert signups went up more than 50% from 475 in 2009 to 935 in 2010.We received 232 submissions this year-a new record for FBR.This includes 163 new submissions and 69 revisions.These numbers represent almost a 30% increase from the previous year, wherein we had received 163 submissions (119 new submissions and 44 revisions).Despite the increased numbers (and thus the volume of work), the overall average response time from submission to decision reduced from 40 days in 2009 to 35 days in 2010.Average reviewer turnaround time remained stable from last year at 18 days.Thanks to the efforts of our conscientious associate editors and reviewers, this turnaround time places FBR among the most efficient journals in management.These noteworthy numbers were achieved because of the dedicated efforts of our 8-member editorial team, 9 advisory board members, a 60-member review board, and 57 ad hoc reviewers.Each of these individuals contributed significantly to help attract good-quality manuscripts to the journal and provide timely and developmental reviews to all scholars who submitted their research for publication consideration to FBR.To recognize the services of our reviewers, in 2009 we initiated FBR's Best Reviewer Awards.As the editorial team conferred to decide the award winners, there were 43 reviewers with perfect score for timeliness and quality of reviews!While it is exciting to have such an amazing level of support from our scholarly community, it certainly made the decision extremely difficult, leading to the inception of Honorable Mention awards.
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 | 0.027 | 0.172 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.017 | 0.016 |
| Insufficient payload (model declined to judge) | 0.034 | 0.044 |
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".