Exploring biometric technology adoption in a developing country context using the modified UTAUT
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
Biometric technology (BT) is a component of information security and person identification. Individual acceptance and adoption of BT is fundamental to successful implementation of BT by organisations. There has been a fairly moderate but improving pace of adoption of technology in developing countries. This study investigates factors affecting users' intention to use BT in a developing country based on the modified version of the unified theory of acceptance and use of technology (UTAUT). Results show that simpler biometric methods (e.g., fingerprinting) have higher level of utilisation than more complex ones (e.g., DNA). The intention to adopt biometrics is influenced by perceived ease of use, security, resource facilitating conditions, self-efficacy, and compatibility. Technology facilitating condition and awareness were found to exert some level of impact, while perceived usefulness, awareness, peer influence and complexity did not show any statistical influence on the intention to adopt BT.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| 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