Putting it together online: Information need identification for the domain novice user
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
Abstract Domain novice users in the beginning stages of researching a topic find themselves searching for information via information retrieval (IR) systems before they have identified their information need. Pre‐Internet access technologies adapted by current IR systems poorly serve these domain novice users, whose behavior might be characterized as rudderless and without a compass. In this article we describe a conceptual design for an information retrieval system that incorporates standard information need identification classification and subject cataloging schemes, called the INIIReye System, and a study that tests the efficacy of the innovative part of the INIIReye System, called the Associative Index. The Associative Index helps the user put together his or her associative thoughts—Vannevar Bush's idea of associative indexing for his Memex machine that he never actually described. For the first time, data from the study reported here quantitatively supports the theoretical notion that the information seeker's information need is identified through transformation of his/her knowledge structure (i.e., the seeker's cognitive map or perspective on the task for which information is being sought).
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.009 |
| Open science | 0.002 | 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