Digital information interaction as semantic navigation
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
In this chapter we focus on the research area of digital information interaction, which emphasizes searchers’ direct engagement with and manipulation of information objects as they search and browse through digital information environments. This is an area of active research that has opened up in recent years as information retrieval (IR) research has expanded its focus from the mechanics of retrieval (i.e. indexing, data structures and retrieval algorithms) to include a broader ‘retrieval in context’ perspective that takes into account the whole system, the affective, cognitive and physical attributes of users and the environment in which searching takes place (Ingwersen and Jarvelin, 2005). A number of meetings and workshops have focused on this area, including the Information Retrieval in Context (IRiX) workshops at the ACM SIGIR (Association for Computing Machinery Special Interest Group Information Retrieval) conference (2004–5), the Information Interaction in Context (IIiX) Conference (2006–ongoing) and the Human Computer Information Retrieval (HCIR) Workshops (2007–ongoing).
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.009 |
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