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Record W7095712496

Farmer Mac’s 2012 Outstanding Business Volume and Core Earnings Reach Record Levels

2013· article· en· W7095712496 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Net incomeEarningsSeveranceAllowance (engineering)PaymentShareholder
DOInot available

Abstract

fetched live from OpenAlex

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

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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.

Opus teacher head0.094
GPT teacher head0.300
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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