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Record W2852215159 · doi:10.5465/ambpp.2018.189

Innovations in the Business Models of Modern Slavery: The Dark Side of Business Model Innovation

2018· article· en· W2852215159 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAcademy of Management Proceedings · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsGreat RiftBusiness modelRevenueValue (mathematics)BusinessBusiness caseNew business developmentBusiness practiceCategorizationMarketingIndustrial organizationComputer scienceAccountingProcess managementBusiness administration

Abstract

fetched live from OpenAlex

This paper addresses the scant attention paid to the dark side of business model innovation by empirically examining innovations in the business models of modern slavery. Our paper focuses on how the business models of slavery in advanced economies like the US and UK have evolved since the practice was legally abolished in the 19th Century. We find that while some continuities with the business models of traditional slavery exist, novel forms of business models have emerged based on new actors, activities, and linkages between activities. We categorize these innovations according to the actor involved (producer/intermediary) and how value is created and captured (revenue generation/cost reduction), giving rise to four innovative models. We discuss our findings considering the literature on business model innovation, the dark side of organizations, and the business of modern slavery, as well as outline implications for policy and practice.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.255
Teacher spread0.211 · 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