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Record W1553270168

Decision-making processes in biotech commercialization: Constraints to effectuation

2012· article· en· W1553270168 on OpenAlex
Elicia Maine, Pek-Hooi Soh, Nancy Dos Santos

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

VenuePortland International Conference on Management of Engineering and Technology · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsBC Cancer AgencySimon Fraser University
Fundersnot available
KeywordsCommercializationCausationVenture capitalContext (archaeology)EntrepreneurshipCircumstantial evidenceNew VenturesBusinessNew product developmentProcess (computing)MarketingComputer sciencePolitical scienceFinanceBiology
DOInot available

Abstract

fetched live from OpenAlex

This research explores two entrepreneurial decision-making processes utilizing effectuation and causation modes in the context of new venture creation in the biotechnology industry. Using a case study approach, we investigate the evolution of three biotech ventures from the start of the venture, featuring major decisions over a period of 10 to 20 years. Assessment of qualitative interviews with founders and CEOs demonstrates that, initially, each company began in effectuation mode and, over time, transitioned to a spectrum between effectuation and causation. The two ventures which retained effectuation logic did not engage in clinical trials. Decision making processes in this study illustrate the interplay between entrepreneurs' ability to manage technological and market uncertainty and circumstantial changes arising from change leadership, venture capital funding and development of lead candidates in the clinical stage of product development.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.269
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