Bibliographic record
Abstract
The arm's-length principle of transfer pricing requires that transactions between related entities be undertaken at prices and on terms and conditions that would exist between entities dealing at arm's length. Applying the arm's-length principle to employee stock options introduces practical and theoretical issues that are difficult to reconcile and resolve. Employers almost never grant options to acquire shares of arm's-length corporations to their employees or to employees of their subsidiaries, since to do so would not serve any incentive alignment purpose. Further, employee stock options are difficult to value because they are explicitly designed to be non-marketable, non-transferable, non-exercisable before vesting, and forfeitable if employment is terminated before vesting. The resulting limited demand for and illiquidity of employee stock options renders their valuation imprecise for all purposes - tax, accounting, and economic. In this article, the authors examine the arm's-length principle and its application to employee stock options in cost-sharing arrangements and recharge agreements between non-arm's-length entities. They also explore the methodology and the timing of valuing such options for the purposes of transfer pricing.
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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 | 0.008 |
| 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 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".