SmartBrowse: Design and Evaluation of a Price Transparency Tool for Mobile Web Use
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
Mobile data use is on the rise globally. In emerging regions, mobile data is particularly expensive and suffers from a lack of price and data usage transparency, which is needed to make informed decisions about Internet use. To measure and address this problem, we designed SmartBrowse, an Internet proxy system that (1) shows mobile data usage information and (2) provides controls to avoid overspending. In this article, we discuss the results of a 10-week study with SmartBrowse, involving 299 participants in Ghana. Half the users were given SmartBrowse, and the other half were given a regular Internet experience on the same mobile phone platform. Our findings suggest that, compared with the control group, using SmartBrowse led to (1) a significant reduction in Internet credit spend and (2) increased online activity among SmartBrowse users, while (3) providing the same or better mobile Internet user experience. Additionally, SmartBrowse users who were prior mobile data non-users increased their web page views while spending less money than control users. Our discussion contributes to the understanding of how ICTD research with emerging technologies can empower mobile data users, in this case, through increased price and usage transparency.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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