Mutual funds that invest in private equity? An analysis of labour-sponsored investment funds
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 paper considers the structure, governance and performance of a unique class of mutual funds that receives capital only from individuals, and reinvests this contributed capital in private companies, as opposed to traditional mutual funds that invest in publicly traded companies. It considers the particular class of mutual funds known as Canadian Labour-Sponsored Investment Funds (LSIFs). In contrast to expectations, it is shown that LSIFs have artificially low betas, returns that have significantly underperformed industry benchmarks, average management expense ratios greater than 4%, and have collectively accumulated $Can10 billion (£4.3 billion) as at 2005 since their statutory inception in various Canadian jurisdictions in the 1980s and 1990s. It is shown that these incongruous data are directly attributable to the LSIF statutory governance structure.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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