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What happened to my Valeant shares?

2016· article· en· W2516734273 on OpenAlexaffabout
Douglas R. McKay, Daniel A Peters

Bibliographic record

VenuePlastic Surgery · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsUniversity of OttawaQueen's University
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

I n a column whose chosen focus is on 'business ' and 'health care in Canada', we would be remiss to overlook Valeant.The complex narrative of this precipitous fall is just so rich with fodder.While each step in the saga could serve as a springboard for discussion (mergers and acquisitions, short-seller attacks, senate investigations, price gouging, questionable accounting practices, hedge fund promotion, shocking market share losses, 'Cold-FX'), it really is more impressive when we run the gamut from start to present.We have been careful not to use the word 'finish'.The resolution may still be years in the making and this will certainly be out of date by the time of publication.This is a story still unfolding, and with that caveat we will do our best to sort through the themes. INCEPTION AND BACKGROUNDValeant is a Canadian company incorporated in British Columbia, headquartered in Laval, Quebec, principally run out of the United States (US), and traded on the Toronto Stock Exchange and New York Stock Exchange.The company arose from the merger of several small pharmaceutical players in the mid 1990s.Its interests are diverse: Valeant manufactures and markets a variety of over-the-counter and prescription medications across a spectrum of subspecialties and diseases.Unlike some of its pharma peers, Valeant eschews home runs for runs batted in.There are few-to-no heavy hitters in its lineup.Consistent niche players make up the team.It is not a research and development-based company; it does not devote years to developing a drug or class, bringing it to market and profiting from proprietary patented protection.Valeant is better thought of as a distributor with the catch that it is a distributor who also owns the patented rights to the medications it sells.How does it come by the product and the patent?Acquisition.

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)0.009
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.183
Threshold uncertainty score0.364

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.005
Scholarly communication0.0100.006
Open science0.0010.002
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0260.005

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 head0.033
GPT teacher head0.222
Teacher spread0.189 · 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
GenreCommentary

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
Published2016
Admission routes2
Has abstractyes

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