Communication ethics and the internet: intercultural and localisinginfluencers
Bibliographic record
Abstract
In the information-technology powered twenty first century a general demand for more effective communication is driving people to question the present, examine the past and to prognosticate the future. The ‘unique global media-information system’ - the Internet- is the central fact of a vast new complexity of communication (mediated and unmediated) that is driving social-economic-political-religious- technological change (see http://www.5systems.net) at a rate never experienced before. The premise of this paper is that the Internet can be better understood as the first complex global media with both democratic and authoritarian possibilities, the full extent of which are still emergent. In respect of the symposium question, this paper suggests that Internet embedded communication theory can be used progressively as part of a widening and deepening approach to intercultural conversation, dialogue and debate. In theory, the localising nature of the Internet can be read as part of a greater movement towards communitarian and community centred self-governance, local democracy and social self-sufficiency. There is considerable scope for a new theory of society founded in localised ‘in-community communication’ practice supported by international human rights and effectively responsive to the asymmetric global information environment and congruent with newly democratised local structures of self-governance.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.067 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".