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.
Bibliographic record
Abstract
Interest in the benefits and drawbacks that stem from the geographic distribution of firms – meaning the socio-economic environment in which they operate – as a potential source of competitive advantage has increased recently in both the entrepreneurship and strategy literature. How those benefits and drawbacks affect de novo firms (independent new ventures) who are considered a major source of job creation, innovation, and economic growth, is not well understood. This dissertation aims to shed light on the processes and conditions underlying de novo firm growth, innovativeness, and the likelihood of transition into the high-growth stage. I draw and integrate theories from strategic management, entrepreneurship, and economic geography and examine these issues using a comprehensive longitudinal data of Canadian manufacturing firms. The insights from my studies are important because they allow us to theoretically and empirically identify and separate the exact locational attributes that affect the growth of new entrants, examine which firms experience the benefits and drawbacks of each attribute, and provide a more complete and systematic explanation of their growth and the determinants of their innovativeness.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it