Reconceptualizing the generation in a digital(izing) modernity: digital media, social networking sites, and the flattening of generations
Bibliographic record
Abstract
Abstract As digitalization binds society to an apparently perpetual acceleration, questions about the nature of time and speed have gained new urgency in the social sciences. Yet, theorizations of these issues have neglected their implications for social life and generations. Linking these lacunae, this article articulates how digital media and social networking sites (SNS) shape social life through cultural transformations in the generation. This article rationalizes predominant patterns of SNS user behaviors in the context of social theoretical and philosophical frameworks informed by Mannheim, Simmel, Adorno, Benjamin, Arendt, social presence, action, and acceleration theories to offer a relational reconceptualization of the generation as a set of social relations and processes for visualizing changing conceptions of time and speed in a digital (izing) modernity. This article introduces the concept of general and local generationing processes to articulate the processual nature of the generation and to assert that trends in SNS use and content production are underwritten by grammatical logics that collectively “flatten” separate traditional generations to form a cross‐demographic and cross‐temporal digital generation.
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 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.023 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".