Bibliographic record
Abstract
The Internet has brought about the emergence of virtual markets with four primary distinct characteristics, which are real-time, shared, open and global (Mohammad, 2003). The growing rate of ICT utilization particularly the Internet has influenced at an exponential rate, online interaction and communication among the generality of the populace. The shortcomings notwithstanding, most people are connected through their cell phones, home PCs and others through corporate access and public kiosks. The patronage of the Internet allover the world is monumental and has remained on the increase from inception. However, with the enormity of businesses on the Internet, Nigeria is yet to harness the opportunities for optimal financial gains. This study is exploratory in nature as it attempts to unveil the prospects of e-commerce participation based on the ability-motivation-opportunity (AMO) framework. The paper proposes to investigate the ability of consumers to purchase online, the available motivation to do so, and the opportunities for Internet access. Findings revealed that Nigerians have the ability to participate in e-commerce, but there is need for improved national image to bring in the element of trust and discipline within, and before the international communities. Furthermore, there is need to encourage public and private initiatives in the provision of the basic infrastructures for improved motivation and opportunities for ecommerce implementation. Currently, consumers source for information online but make purchases the traditional way.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".