Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
How does bundling affect valuation? This research proposes the asymmetry hypothesis in the valuation of bundles: consumers demand more compensation for the loss of items from bundles, compared with the loss of the same items in isolation, yet they express lower willingness to pay for items added to bundles, compared with the same items purchased separately. This asymmetry persists because bundling causes consumers to perceive multiple items as a single, inseparable gestalt unit. Thus, consumers resist altering the “whole” of the bundle by removing or adding items. Six studies demonstrate this asymmetry across judgments of monetary value (Studies 1 and 2) and (dis)satisfaction (Study 3). Moreover, bundle composition—the ability of different items to create the impression of a “whole”—moderates the effect of bundling on valuation (Study 4), and the need to replace missing items (i.e., restoring the “whole”) mediates the effect of bundling on compensation demanded for losses (Study 5). Finally, the authors explore a boundary condition: the effect is attenuated for items that complete a set (Study 6).
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.180 | 0.162 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it