University Students' Local And Distant Social Ties: Using and integrating modes of communication on campus
Bibliographic record
Abstract
The use of the Internet has increased dramatically in recent years, with university students becoming one of the most dominant user groups. This study investigated how the Internet is integrated into university students' communication habits. The authors focused on how online (email and instant messaging) and mobile (cellphones and texting) modes of communication are used in the context of offline modes (FTF and telephone) to support students' local and distant social ties. Using a mixed methods approach that combined survey data from 268 Canadian university students with focus group data, a rich description was obtained of what modes of communication students use, how they integrate them to fulfill communication needs, and the implications of this integration for the maintenance of social ties. It was found that friends were the most important communication partners in students' everyday lives. Regardless of the type of social tie, instant messaging was used the most for communication. Because of their high cost, the cellphone and texting were used less. Increased distance between communication partners reduced communication – local communication was more frequent for both friends and relatives. While instant messaging and email were used less for contact with those faraway, the decrease was not as sharp as with in-person and telephone contact. In particular, instant messaging was used extensively for distant contact with friends – often daily. While online modes were used widely for local communication, it was evident that they also filled communication gaps with those faraway. Because they were inexpensive and readily available on campus, email and instant messaging were highly used by students and they facilitated a close integration of far-flung ties into university students' everyday lives.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".