Software Piracy and Ethical Decision Making Behavior of Chinese Consumers
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
China has one of the highest software piracy rate in the world. It is important to understand consumers' ethical response to software piracy in the Chinese markets and design effective preventive strategies. This paper proposes a conceptual framework for an understanding of consumer ethical decision making. In the proposed framework, the transformation from legal problem recognition to ethical problem recognition is added to the traditional research framework and viewed as the first and most important step in consumer ethical decision making in regards to software piracy. The effects of two culture-related constructs— assumption of responsibility and attitude towards copyright laws on consumer ethical decision making— are examined and two propositions are made. The influence of Chinese culture and history on consumer ethical decision making is discussed. This paper contributes to our understanding of consumer ethical decision making in software piracy and provides new and constructive interpretations of the cultural influence.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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