Professional flows: Lateral moves of law firm partners in Hong Kong, 1994–2018
Bibliographic record
Abstract
Abstract This article uses the case of law firms in Hong Kong to develop a processual approach for understanding lateral mobility in professional service firms. Based on the analysis of 1,461 lateral moves of law firm partners reported in 300 monthly issues of the official journal of the Law Society of Hong Kong during 1994–2018, as well as archival data and interviews conducted in Hong Kong, the article offers both a bird’s-eye view of the lateral mobility of partners across law firms of different jurisdictional origins and an in-depth investigation of how elite law firms in this market, namely the Magic Circle and Wall Street firms, are influenced by the dynamics of professional flows. Theoretically, the article reconceptualizes professional service firms as organizations connected by and transform through the flows of professionals between them, a dynamic process characterized by three key concepts: waves, cycles, and turning points. In addition to its theoretical contribution, the study has broader implications for understanding Hong Kong’s economic transformation since the 1990s, particularly after Hong Kong’s handover to China in 1997 and the global financial crisis in 2008.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".