From Business Owner with Zero Assets to Full-time Investor with Over 4,000 units with Darin Batchelder
Bibliographic record
Abstract
Darin Batchelder decided to get involved purchasing real estate in the fourth quarter of 2017. He purchased a new construction duplex, but then searched for a way to go after larger deals. He was very familiar with the multifamily asset class but wanted to learn how to purchase larger deals. He joined a multifamily mentorship group in the Dallas area and by the beginning of 2018 he started to invest passively into other sponsors multifamily deals as well as started to underwrite and go after his own lead sponsor deal. He closed his first lead sponsor deal at the end of 2018 which was a 76 unit townhome community. In total he's invested in over 4,000 multifamily units- seven deals passively with other sponsors, one deal as the lead sponsor, and one deal with two well established general partners for a small minority stake in the deal. Book Recommendations: The Honey Bee by Jake Stenziano and Gino Barbaro, Tools of Titans by Tim Ferriss Prayer Requests: Strengthening of relationships with wife and kids Connect with Darin: Website: https://darinbatchelder.com/, LinkedIn: https://www.linkedin.com/in/darin-batchelder-8855b620/ Connect with Lee: Website: threefoldrei.com, Email: info@threefoldrei.com, Phone: 937-400-3044
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.114 | 0.006 |
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; both teacher heads agree on what is shown here.
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".