Farmer Mac’s 2012 Outstanding Business Volume and Core Earnings Reach Record Levels
Bibliographic record
Abstract
and AGM.A) today announced that it achieved record business volume and core earnings for the year ended December 31, 2012. Farmer Mac’s outstanding business volume, consisting of loans, guarantees, and commitments, rose to $13.0 billion as of December 31, 2012, up from $11.9 billion as of December 31, 2011. Farmer Mac’s 2012 core earnings, a non-GAAP measure, increased 15.7 percent to $49.6 million ($4.51 per diluted common share), continuing the upward trend from $42.9 million ($3.97 per diluted common share) in 2011. Farmer Mac’s core earnings for fourth quarter 2012 were $11.6 million, compared to $12.6 million for fourth quarter 2011. Core earnings for 2012 benefited from higher net effective spread of $106.6 million (95 basis points), compared to $89.4 million (96 basis points) in 2011. This higher net effective spread was partially offset by net provisions to the allowance for losses of $1.9 million in 2012, compared to net releases from the allowance for losses of $2.3 million in 2011. Both GAAP net income and core earningsfor fourth quarter and full year 2012 were negatively affected by the severance payment made to a former executive in connection with the termination of his employment in October 2012, which resulted in a net after-tax expense of $1.0 million during fourth quarter 2012. Farmer Mac’s GAAP net income attributable to common stockholders was $9.6 million ($0.87 per diluted common share) for fourth quarter 2012 and $43.9 million ($3.98 per diluted common share) for
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.069 | 0.022 |
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 source (direct Gemma or distilled Codex), 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".