Selecting a suitable technology: it's about people and their tasks
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
This paper reports the outcome of a user-context analysis of two interactive devices used by product assemblers in a large grocery distribution warehouse in Ottawa, Canada. One used a screen-based textual platform and a handheld device, and the other was speech-based. The former had been in use in the centre for some time, but management was trialling hands-free Interactive Voice System (IVS) at the time the study took place, to help them decide if the hand-held display units should be phased out throughout the centre. The IVS was a small battery-operated computer with scanning capabilities that acted as an interface to the backend Warehouse Management System (WMS) and the user. The hand-held device had a keypad and a barcode reader for data entry as well as a small screen display. Two versions of this technology were in use at the time, displaying either six or eight lines of text in a serif font. Both displays used a serif font. Findings showed that the main problems were less with the technologies than with work-related user performance requirements that revealed certain negative effects outlined in the paper. It was concluded that user experience theories and models in the current literature were inadequate for guiding the research, and that the HCI community needs to adopt a more nuanced approach to the definition and measurement of the user experience construct.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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