Platform Visibility and Creative Autonomy among Malaysian Independent Illustrators

This paper examines transparent portfolio discovery rules in relation to creative autonomy score in a setting motivated by Malaysia. The objective is to develop an classroom research example and test an analysis strategy before field implementation. The proposed mechanism is that predictable discovery rules may protect experimentation by reducing the pressure to imitate immediately popular styles. A reproducible numerical exercise generates 144 case observations with balanced intervention allocation, a standardized baseline variable, a binary contextual support variable and a continuous illustrative outcome index. An adjusted linear model estimates the intervention contrast at equal contextual support, while a bootstrap provides a second uncertainty assessment. The illustrative adjusted contrast is 2.86 index units, with an approximate 95% confidence interval from 0.60 to 5.12; the corresponding unadjusted contrast is 3.08. Five effect scenarios, each repeated 200 times, assess estimation bias, root mean squared error and interval coverage. The analysis demonstrates how baseline variation and income stability can be represented in a transparent preliminary design. It does not estimate an actual effect in Malaysia, validate the proposed measurement instrument or establish operational effectiveness. The paper contributes a topic specific intervention rationale, an auditable numerical demonstration and a field validation plan. Practical recommendations focus on measurement quality, implementation responsibility and careful interpretation of estimates and outcomes. Further research should calibrate assumptions with real data and examine whether implementation costs and distributional burdens alter the proposed decision.