MétaCan
Menu
Back to cohort
Record W7132603573

Scanteak: The Making of Successors in a Family Firm (A)

2019· other· en· W7132603573 on OpenAlexaff
Siew Kim Jean Lee, Liman Zhao, Yunting Lu

Bibliographic record

VenueCEIBS Institutional Repository · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsCorporationPromotion (chess)Family businessMaking-ofBig businessTicket
DOInot available

Abstract

fetched live from OpenAlex

Singapore Scanteak Corporation (Scanteak), a furniture retailer founded in the 1970s, had more than 100 stores around the world by 2010, becoming the first furniture company to be listed on the Taiwan Over-The-Counter (OTC) Exchange. Along with corporate development, the founders, Pok Chin Lim and his wife, Catherine Foo, invested a lot in their children, especially in educating them as the successors of the company. In 2003, Lim asked his elder daughter, Jamie Lim, to help with growing family business. Over the next seven years, Jamie made big achievements in brand promotion and market expansion. In 2010, Lim asked his son, Julian Lim, to help with the business in Singapore or Taiwan, from where he wanted to train Julian up. However, Julian, who had always followed his parents' wishes, rejected their offer, and would agree only if he could independently run the Scanteak business in Japan, which was in deficit. The Lims questioned whether their newly graduated son could handle the business in Japan, and wondered how to respond to their son's bold request.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.082
Threshold uncertainty score0.273

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.003
Scholarly communication0.0080.006
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0820.015

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 head0.018
GPT teacher head0.268
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCEIBS Institutional RepositoryFrench-language works237,207