Bibliographic record
Abstract
Seldom has the arc of a neologism been so visible. On the afternoon of August 18, 2007, standing at the PodCamp Pittsburgh registration desk, Tommy Vallier, Andy Quale, Ann Turiano, Jesse Hambley, and Val and Jason Head—all participants in the city’s annual social media conference—were having a conversation about Canadian bacon. Vallier informed the group that peameal bacon was an alternate name for the breakfast meat, leading others to comment that peameal sounded like email. This coincidence in turn reminded them of a prior discussion about all the automatic email notifications they received daily, from Google news alerts to Facebook updates, which were becoming almost as distracting as spam. They decided it was a problem, and their banter about peameal and pork suggested a name. Since the notifications were a cut above spam—after all, these updates had been requested—they dubbed this “middle class” of email bacn. The following day the six PodCampers held a spontaneous group session with several dozen of their fellow social media mavens, who were swiftly won over by the jokey name and ironic spelling (a play on sites such as Flickr and Socializr then popular). The web address bacn2.com was acquired—bacn.com was already taken by a bacon distributor and bacn.org belonged to the Bay Area Consciousness Network—and a droll public service announcement explaining the time-wasting dangers of bacn was promptly posted on YouTube. What happened next was best explained by PodCamp’s cofounder Chris Brogan to the Chicago Tribune five days later. “The PodCamp event was about creating personal media,” he said, “so 200-something reporters, so to speak, launched that story as soon as they heard it.” The term was written up on hundreds of personal blogs, bringing it into Technorati’s top fifteen search terms and leading Erik Schark to muse on BoingBoing that the spread of bacn showed “the ridiculous power of the internet.” Schark also listed the mainstream media that had covered it, including CNET, Wired , and the Washington Post, where Rob Pegoraro complained about the name: “Bacon is good,” he opined.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.553 | 0.379 |
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".