One Step Closer to the Field: Visual Method in Marketing and Consumer Research
Bibliographic record
Abstract
The purpose of this study is to examine the use of visual research methods in the area of recent marketing and consumer research. All articles published in Journal of Consumer Research (JCR), Journal of Marketing (JM), Journal of Marketing Research (JMR), Journal of Marketing Management (JMM), Consumption, Markets, and Culture (CMC), and Qualitative Market Research (QMR) from year 2002 to 2010 were examined. A total of one hundred and twenty two articles with images or pictures were selected for further analysis. This study found that a total of sixty research studies employed photograph or video as ‘projective stimuli’, a total of forty four research studies used ‘cultural inventories’, and seven research studies employed ‘social artifacts’. Overall, this study found that a growing number of marketing and consumer researchers utilize visual methods in various ways to achieve their research goals
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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 | 0.042 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".