Bibliographic record
Abstract
Introduction An insurance company is a financial intermediary whose main line of business is the sale of a particular type of contingent contract, called an insurance policy. Under this contract, [in return for the premium], the insurer promises to pay some amount to the policy-holder, or to some other beneficiary, following the occurrence of an insured event. For VAT purposes, most countries lump together insurance and financial services rendered by financial institutions. The typical pattern is to include insurance within the definition of exempt financial services. There are some exceptions. Israel does not tax insurance under its VAT. Rather, it taxes insurance companies under a system administered by the income tax department. The Israeli tax is calculated under an addition method that includes wages and profits in the tax base and does not allow any deduction for VAT paid on business inputs. In effect, Israel imposes tax on the full value of insurance services. New Zealand taxes insurance other than life insurance under its GST. South Africa and several other countries follow the New Zealand pattern of taxing the value added by property and casualty insurance companies, on the basis of the margin between premiums received and claims paid.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.063 | 0.027 |
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".