Bibliographic record
Abstract
Online networks and digital media have been integrated into contemporary processes of dying and memorialization, changing the social context in which dying takes place and establishing new memory culture. This paper, thus, examines the relation between media and memory through the case of war dead commemoration in Vietnam. As tens of thousands of Vietnamese died in military service during the war, their commemoration has been an important issue both inside and outside academia. This memory of the harsh past continues to be transmitted, historically and psychologically, through generations. Considered to be a flexible, individualized, decentralized, a-historic medium, how has the media environment contributed to the construction, reconstruction and representation of memory in Vietnam? My central argument is that, with a wide range of users, and various tools and forms of communicative interaction, internet-based media enables actors who are not part of the traditional institutions regulating the discourses about the past to constitute remembrance beyond the official narratives promoted by the authorized agents. Also, within such electronic spaces, it is pivotal to highlight the dynamics of memory which overcomes the temporal and spatial distance between the situational of remembering and the past events which are remembered. This feature of online memorialization and mourning practices, hence, poses a question to the philosophy of personal identity. While the dead somehow live on through their online presence, how do specific features of online social networks affect the ontology and embodiment of them?
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".