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
This article analyzes the patterns of financing for entrepreneurial firms in Canada. We compare the predictions of major theories of entrepreneurial finance and some more recent ideas (e.g., crowdfunding-related ideas/theories) with empirical evidence. Regression and correlation analyses were used to analyze the connections between firms’ financing choices (e.g., debt/equity ratio) and different variables such as firm age, firm owner origin, and the fraction of intangibles assets. We found strong evidence that the financing choices of entrepreneurial firms in Canada are consistent with flexibility theory and credit rationing theory. We did not find evidence that taxes play a significant role in explaining these choices. We also found that the likelihood of using crowdfunding is consistent with local bias ideas and internet access. We also provide an overview of literature related to entrepreneurial financing in Canada and discuss its major challenges and directions for future research.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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