Efficient Timing of Communication in Multiperiod Agencies
Bibliographic record
Abstract
This paper examines communication in a two-period principal/agent model in which the agent receives a private signal about the second outcome before the first outcome is realized. No communication is compared with communication at three possible dates: before the first outcome (early), at the first outcome/consumption date (normal), and between the initial consumption date and the second outcome (delayed). Delayed communication is shown to have no value if the agent's information is perfect, but can have value if it is imperfect. Early and normal communication can be used to “smooth” compensation across periods and, hence, generally have incremental value over delayed communication if the agent cannot borrow or save. However, the “smoothing” benefits disappear if he can borrow and save. Early and normal communication are equivalent if the agent has domain-additive exponential preferences and the private signal is uninformative about the first outcome. If the private signal is informative about the first outcome, the incremental value of early compared with normal communication attains its maximum for “medium” informativeness. A unifying example is used throughout.
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".