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Record W7132545358

Smart Health (B): Negotiation with a Social Purpose

2020· other· en· W7132545358 on OpenAlex
Byron Y. Lee, Liman Zhao

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

VenueCEIBS Institutional Repository · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsCentre Casa
Fundersnot available
KeywordsNegotiationOrder (exchange)Perspective (graphical)Profit (economics)Venture capitalProfit motiveControl (management)
DOInot available

Abstract

fetched live from OpenAlex

This case describes the background to an upcoming negotiation between a Chinese social entrepreneur (Jamie Zheng) and a venture capitalist (Chris Liu). Case (A) lays out the situation from the perspective of Jamie, who is attempting to attain first-round investment in order to better grow Smart Health, which was founded by Jamie. However, Jamie's purpose for the firm includes not only the pursuit of profit but also a desire for the firm to have a social impact by making life easier for the elderly. This provides a potential conflict, as Jamie’s social purpose may impede the company’s commitment to the pursuit of profit. After negotiating with five investors, Jamie still could not reach an agreement, especially with Smart Health’s social goal being an important condition for its future development. However, Jamie is optimistic heading into this meeting with Chris, as Jamie believes Chris shares the same vision and understands the unique nature of Smart Health as a social enterprise. Case (B) presents the perspective of Chris, who, on a personal level, likes Jamie’s idea of helping the elderly. However, as a traditional venture capitalist and an agent of XYZ Capital, Chris understands the importance of investing in firms based on their potential profitability. Therefore, Chris needs to ensure a sound return on investment, which includes some control over how the firm makes financial decisions in the future. Students will be asked to play the role of either Jamie or Chris and negotiate on how they can come to an agreement on the venture capital firm’s potential investment in Smart Health and what degree of control the venture capital firm should have over Smart Health, in order to ensure it meets its financial obligations. They must haggle over one issue—social purpose/goal. The key question for this negotiation is: How does one reach a deal when there is more than just a financial incentive at stake? How does one negotiate when the social purpose of the firm is among the issues at hand? The hybrid nature of a social enterprise adds exponentially to the difficulties of reaching a negotiated deal with any investor. Social enterprises face the inherent paradoxical tensions of creating dual value (i.e., social value and economic value). On the one hand, social enterprises are driven by the nature of the desired social change. We call this the social purpose (or social mission, goal, or objective). On the other hand, and no less important, is the need for the social enterprise to be at the very least sustainable or creating value through market means. Given these two goals, the negotiation between a social enterprise and an investor is complicated. How should social goals/purpose be valued? How is this valued differently for the investor? How should the financial and social goals of the social enterprise be balanced? What are the tradeoffs? How social enterprises manage these tensions is considered in this negotiation case and is an important issues that is commonly encountered by social enterprise’s especially during the process of considering venture capital funding.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.015
GPT teacher head0.246
Teacher spread0.231 · 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

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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