International strategic alliances of small biotechnology firms: a second-best option?
Bibliographic record
Abstract
International strategic alliances have often been presented as the main growth factor for dedicated biotechnology firms (DBFs). Alliances bring resources such as complementary knowledge and financial resources to DBFs. They help these smaller firms conduct R&D, and costly and long clinical essays and regulations. They build bridges with foreign capital and product markets. Even if some authors have noticed that alliances are not always beneficial or feasible, the main picture has not been altered: they are still presented as a bounty for smaller R&D biotechnology firms. Our research, based on in-depth interviews of samples of DBFs in Montreal and Boston, suggests that, in both clusters, they use alliances as a second-best option. The preferred strategy is to conduct in-house R&D supported by venture capital and capital market funds, and only sign alliances at the latest possible time, in order to complete the R&D process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".