HONR 300Ab (AH) The dangerous art of truth-telling and truth-seeking Benedix Spring 2024
Bibliographic record
Abstract
Canadian journalist Terry Glavin made a statement on a recent episode of the podcast, “Honestly,” that has been plaguing me: “what I find more troubling than the fact that the truth doesn't seem to matter [with regards to media] is that it doesn't seem to matter that the truth doesn't matter.” I find this troubling, too. How can the truth not matter? And yet, in so many spheres--politics, education, media--truth often seems to be subjugated to confirmation bias. My first impulse in creating this class led to the title “The (dangerous and outdated?) art of truth-telling and truth-seeking.” I don’t like that title anymore. It feels glib and cynical. Upon further reflection, I don’t think the art is outdated in any capacity. Everywhere I look, I see evidence of people—artists, musicians, writers, comedians, activists, journalists, chefs, kids, teachers, students, my very best friends (!)—speaking truth to power, who courageously enact the conviction that they have something to say that the world needs to hear, who earnestly believe that hearing this truth will make the world a better place. I kept “dangerous,” but took the question mark away, because there’s no question that, in today’s climate (and maybe from the beginning of time), it is dangerous to speak truths that people don’t want to hear. I have two main hopes for this class: 1) that we’ll explore the wide terrain of truth-telling/truth-seeking, in the efforts of identifying voices/styles/approaches that resonate (and/or don’t) and identifying patterns in texts (broadly defined) that claim (or seem to claim) to be telling the truth, and 2) that, by the end of the semester, we’ll have a set of products (broadly defined), collectively and independently created by everyone, that we can share with a general audience. The mission: to nail down slices of truth(s) that we think desperately need to be brought into the world, packaged in a way that people will really hear and contemplate what we’re saying. The second half of the semester will include planning and implementing an event that will invite an audience into this space of truth-telling/hearing.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.471 | 0.244 |
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".