How is a search system used in work task completion?
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
Typically studies of information retrieval and interactive information retrieval concentrate on the identification of relevant items. In this study, rather than stop at finding relevant items, we considered how people use a search system in the completion of a broader work task. To conduct the study, we created 12 tasks that required multiple queries and document views in order to find enough information to complete the task. A total of 381 people completed three tasks each in a laboratory setting using the wikiSearch system that was embedded into WiIRE. Results found that two-thirds of time spent on the task was spent after finding a relevant set of documents sufficient for task completion, and that time was mainly spent reviewing documents that had already been retrieved. Findings suggest that an open-source information retrieval system, such as Lucene, was adequate for this task. However, the ultimate challenge will be in building useful systems that aid the user in extracting, interpreting and analysing information to achieve work task completion.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.027 |
| Open science | 0.001 | 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