Bibliographic record
Abstract
In the context of transformation of the digital advertising ecosystem driven by tightening regulatory norms and increasing user attention to personal data protection issues, the question of counteracting blocking of targeted advertising becomes especially relevant. The aim of the study is to construct and methodologically substantiate a holistic model capable of ensuring the resilience of targeted advertising strategies to blocking under strict requirements for protecting the confidentiality of user data. The methodological basis of the work includes a comprehensive analysis of profile scholarly publications, examination of key regulatory acts (in particular, GDPR and DMA), as well as analysis of practices and policies of leading global technology companies. The scientific novelty of the research consists in proposing an integrated strategic model of proactive compliance combining technical, ethical and creative components in a unified targeting management system, instead of the widespread reactive and narrowly focused solutions. The proposed model demonstrates that stable effectiveness of targeted advertising is ensured not by attempts to circumvent restrictions, but by building long-term engagement based on principles of transparency, mutual respect and value exchange. The practical significance of the work lies in the fact that its results may be used by marketers, digital communications specialists, advertising technology developers and scholars in the field of media communications to create more sustainable and ethically grounded advertising campaigns.
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.
How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".