A Cross-National Comparison of Intragenerational Variability in Social Media Sharing
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
Given Millennials’ early digital life experiences, the adoption of social media tends to be greater among members of this generation compared to older ones. However, studies that report such age-based generalizations tend to neglect the phenomenon of intragenerational variability in social media use, providing an oversimplified picture of how people behave. Moreover, studies that compare social media use across nations are lacking, and are also needed to establish the generality of this phenomenon. This paper investigates intragenerational variability in social media sharing among Millennial travelers in six nations (Canada, France, India, Japan, Mexico, and USA) using Destination Canada’s Global Tourism Watch database. A latent class segmentation model is used to identify groups of travelers with different ways of using social media to share trip experiences. Results supported five unique classes of social media sharing, ranging from nonuse to highly integrated sharing across many platforms. Additionally, class membership is predicted by covariates (nationality, travel experience, and social media use and goals) and is predictive of destination advocacy (offering recommendations). The identification of different classes of social media sharing advances theory on intragenerational and cross-national variability, and informs the development of international strategies that target Millennial travelers based on their tendency to share and advocate.
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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 | 0.024 | 0.010 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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