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Record W2783428967 · doi:10.1123/cssm.2017-0017

Investing in Sports Stocks: A Case of Sportfolio Management Inc.

2017· article· en· W2783428967 on OpenAlexaff
Chris Chard

Bibliographic record

VenueCase Studies in Sport Management · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsBrock University
Fundersnot available
KeywordsHedge fundInvestment managementBusinessOfficerInvestment (military)FinanceChief executive officerManagement feeReturn on investmentInvestment strategyEconomicsManagementInstitutional investorOpen-end fundCorporate governanceMicroeconomics

Abstract

fetched live from OpenAlex

Jordan Bourne is the Chief Executive Officer (CEO) of Sportfolio Management Inc. (SMI), a small hedge fund operating out of Boston, Mass. SMI provides prudent and profitable investment management services to clients through active investment in publicly traded companies operating in sport-related business endeavors. By employing both “long” and “short” investment management strategies, Bourne’s objective is to achieve a positive rate of return in the Sportfolio for her valued clients. Assistance from the firm’s Investment Analysts is vital to meet this objective.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.003
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.099
GPT teacher head0.384
Teacher spread0.285 · 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 designCase report
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

Citations0
Published2017
Admission routes1
Has abstractyes

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