Critical Mass: The Listserv And The Early Online Community As A Case Study In The Unanticipated Consequences Of Innovation In Scholarly Communication
Bibliographic record
Abstract
Scholarly Communication today exists in a state we might best describe as ‘revolutionary stasis’. On the one hand, it is hard not to be impressed by the disruptive potential networked computing brings to the way researchers disseminate their results. The development of the Web twenty-six years ago ushered in a period in which scholars could organise, collaborate, and publish in fundamentally different ways than any time previously. There are new economic models for scholarly publishing, new models for career evaluation and progress, and new understandings of the relationship between scholars and the general public. At the same time, however, given this revolutionary potential, it is also hard not to be impressed equally by the difficulty these new ideas have had in actually disrupting pre-web ways of working. Indeed, in many cases, traditional markers of success and prestige have become if anything even <em>more</em> tenacious and entrenched than they were before Tim Berners-Lee first rolled out the Word Wide Web in early 1991. While there has been a slow-but-steady rise in the number of Open Access journals, academic publishing is still dominated by the same few presses (e.g., in the Humanities, Oxford, Cambridge, Blackwells, Routledge). Groups like the Modern Language Association (MLA) have worked to develop new forms of evaluation to accommodate new digital and collaborative forms of scholarship, even as measures of impact that focus on secondary and more traditional markers of use or prestige—such as the citation count or journal impact—have become increasingly important through national evaluation schemes such as the United Kingdom’s Research Excellence Framework or the Excellence in Research for Australia. In this paper, I argue that this frustrating state of affairs stems from a misunderstanding of how technological change works in Scholarly Communication. Although it is very tempting to assume that new platforms, methods of working, or economic models will replace their traditional counterparts, the experience of the last thirty years has demonstrated that new developments in this space tend to be complementary rather than competitive—that is to say that they introduce additional channels of communication or ways of working rather than replace existing ones. In this sense, our frustration with the degree to which technology has not changed scholarly communication may be because we are looking for the change in the wrong places: it is by supplementing and building on what came before, rather than, for the most part, replacing previous methods in fundamental ways, that such innovations ultimately change the way we work.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".