Bibliographic record
Abstract
One of the matters that seem to preoccupy all the more the researchers of ICT and the sociologists, along with the parents and teachers, is the relationship between the child and the products of new age technology, especially the internet. And the results this relationship could have in personal and social level in important institutions like family and teaching and in important functions like writing and speaking. Having the study of the representations an important field of the social and anthropologic research the recent years, able to offer in the comprehension of the social operations and the relations of power they encompass, email language is proven all the more a rising field of research. This is not only attributed into the “inner status itself” of the email that offers a combination of “writing” and “oral” logos along with “new technology”, but is equally attributed into the “external dynamics” that the social subjects whom correspond carry into the e-mail communication.. Because as email brings “together” persons from a diversity of origins and a variety of cultures, its language is filled with various social, cultural and psychological connotations. All the more, having western world the recent decades (due to mass immigration and the intercultural societies that were evolved), to meet “the disappearance of the Self and the State” as we knew it, it is worth trying to explore the dynamics of this procedure using one of society’s orienting concepts. Communication. In this framework an email correspondence between a girl of Greek origin living abroad (a girl from “Diaspora”) and a native Greek girl seems an intriguing case of research but also a case that requires an equally complicated method of analysis. Using a synthetic method, (combining the theories of Wierlacher, Gennete and Bachelar), in other words a method able for us to bring forth not only the linguistic but also the psychological parameters that intervene in correspondences between people of different sub-cultures, we tried primarily to exhibit the complexity of those correspondences and secondly to locate interesting data. We should point though, that this was an experimental research from the point of humanities, and more specifically from the point of Intercultural Linguistics, in a brand new field and we should wait the new researches that already follow to justify or un-justify its results. In both cases this research probably will prove its value being one of the first question marks in a strange yet exciting new field of interest.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".