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Record W4403890596 · doi:10.1017/lsr.2024.25

Crisis as opportunity: legal career paths at two historical turning points in Hong Kong

2024· article· en· W4403890596 on OpenAlexaff
Sida Liu, Anson Au, Pamela P. Tsui

Bibliographic record

VenueLaw & Society Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicComparative and International Law Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTurning pointSociologyPolitical scienceLawCriminologyPsychologyPeriod (music)Art

Abstract

fetched live from OpenAlex

Abstract This article investigates the career trajectories of Hong Kong solicitors during two historical turning points, specifically 1994–1997 and 2018–2021, when hundreds of lawyers left private practice to pursue alternative career options such as business and finance, government and politics, or relocation to other countries. Data are sourced from the career mobility records of law firm partners reported in 336 monthly issues of the Hong Kong Lawyer journal between 1994 and 2021, as well as other relevant archival sources. The research examines the underlying forces that led these law firm partners to abandon their high-status positions and pursue alternative career paths during these pivotal moments in Hong Kong’s history. The findings suggest that the career trajectories of these elite professionals are not solely based on individual choices but are also shaped by their social origins and the physical and social spaces that influence their careers over time. This study contributes original insights into the complex interplay between individual, spatial and temporal factors that drive career mobility among legal professionals.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.603

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.090
GPT teacher head0.382
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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