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
Small industries tend to achieve marketing performance harder than their bigger counterparts, constrained by limited resources when compared to large businesses, especially during the Covid-19 pandemic. These constraints seem to still be relatively difficult to find a way out and result in low marketing performance including small industries in Denpasar. The purpose of the study is to explain the influence of entrepreneurial personality on marketing performance and to investigate the role of digitalization of marketing as a moderation of the influence of entrepreneurial personality on the marketing performance of small industries in Denpasar. The subject of the study was a small industry in Denpasar, represented by the owner / manager as a source. The sample size was set at 150 respondents. Analysis techniques use Moderated Regression Analysis (MRA). The results found that entrepreneurial personality has a significant influence on marketing performance, and digitalization of marketing acts as a quasi-moderation of the influence of entrepreneurial personality on the marketing performance. Small industries should be more active in exploring paid online media since it has a wider reach, such as existing market places or utilizing government-provided facilities, be careful about setting production targets and setting targets for special forces on marketing performance.
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 | 0.007 | 0.001 |
| 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 | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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