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Record W2478578334 · doi:10.1142/9789812770318_0002

KNOWLEDGE CREATION DYNAMICS AND FINANCIAL GOVERNANCE: CRISIS OF GROWTH IN BIOTECH FIRMS

2007· book-chapter· en· W2478578334 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueManagement of technology · 2007
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsBusinessCorporate governanceFinancial crisisDynamics (music)Financial systemAccountingFinanceEconomicsSociology

Abstract

fetched live from OpenAlex

AbstractThe business models of dedicated biotech enterprises currently focus on the management of inventions with the aim of entering a virtuous growth cycle based on judicious directing of R&D projects (towards the market), the choice of intellectual property to be protected and traded, as well as managing financial options. We here deepen our understanding of the technological and organizational development cycle of these firms. We base ourselves on a series of semi-structured interviews with over 110 biotechnology firms within Quebec, one of the largest bio-cluster in Canada. This exploratory field study leads us to major paradoxical observations between organizational knowledge creation within biotechnology firms and the type of financial governance that is present. It ultimately shows three different modes of development within those firms: that is, pre-entrepreneurial, entrepreneurial and managerial, each staking out the progress of biotechnology firms, and also equally marked by two transformational ruptures (teleological and creativity gaps).

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score1.000

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 science0.0000.001
Research integrity0.0010.000
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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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