CUTTING ACROSS: Identities and Digital Marketing
Bibliographic record
Abstract
This Major Research Project (MRP) looks at the intersection of digital marketing and identities, amongst liminal persons and those who have multiple identities. In Les Rites de Passage, 1909, Arnold van Gennep introduced the concept of liminality as the transition between two social states, such as entering a new life stage. My research also builds upon Victor Turner’s concepts of liminality, identity transformation, and multiple personas. In digital worlds, liminality and identity play are common practices. As the internet faces further commercialization and transformation (e.g., regulation, data management, new social platforms), marketers need to better understand identity management. \n \nMarketing and communications platforms shape identity and influence behaviour. Marketers track personas, which lay the basis of assumptions and decision-making. Digital marketing has transformed our ideas of self and individual representation, often serving corporate goals. Those who are marginalized are often over surveilled or completely unaccounted for, creating misrepresented customer profiles. \n \nResearch with marginalized individuals in Canada was conducted to understand their multiple identities, digital lives, and liminality. Interviews, digital diaries, and foresight scenarios illuminated influences on how digital identities are formed and managed. Marginalized groups are more vulnerable to the negative impacts of digital marketing, such as discrimination, highlighting pertinent ethical concerns and leverage points for improvement. \n \nThis MRP’s insights inform digital marketing and market segmentation to ensure ethical and human-centred practices that respect the individual. The recommendations address how digital marketing can adequately account for the plurality of individuals, and how people undergo constant identity change. The most desirable future of identities is one that is transformational, exhibiting sovereignty over one’s multiple identities. This includes three key themes — identity construction, social relationships, and financial and transactional implications — to reach a more equitable identity ecosystem.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.022 | 0.017 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".