Robin Mansell: Imagining the Internet. Communication, Innovation and Governance. Oxford: Oxford University Press. 2012
Bibliographic record
Abstract
From its very beginnings, the Internet's development has been marked by competing visions of its social function and business potential.Whereas some (mostly early computer experts and users) saw in the Internet the materialization of an open, freely accessible information and communication network with democratizing effects, others wondered about the business value of this technology.In her overview of the history of the Internet, Janet Abbate (2001) reminds us that "the priorities, re-sources, constraints, and beliefs of the academic researchers who created nonprofit networks in the 1960s were different from-and, in some respects, explicitly opposed to-those of the commercial computing and communications industries" (p.149).Imagining the Internet takes up these competing visions today, examining the way in which they are framing Internet debates in the realm of policymaking.A respected political economist of communication, LSE Professor Robin Mansell's approach to thinking about Internet policy debates by drawing from the literature on "social imaginaries" and from systems theory promises to bring a much needed attention to both discourses and complexity in tackling policy-making.For Mansell, contemporary social imaginaries of the Internet are framed by two conflicting visions: information scarcity and complexity paradoxes.The paradox of information scarcity refers to the high reproduction/low distribution cost of digital information.As the abundance of digital information threatens the profit of the digital information production and distribution sectors, companies in this line of business seek to impose a regime of information scarcity via copy- Delia Dumitrica
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.019 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.025 | 0.010 |
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".