“There’s a Rule Book in my Head”: Journalism Ethics Meet A.I. in the Newsroom
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The burgeoning use of artificial intelligence (A.I.) to create journalistic products is challenging the ethical standards in Canadian newsrooms and calling into question the efficacy of existing norms and practice worldwide. Ethical literacy related to the use of A.I. remains low in the industry at large, and with no standardized ethical practice, there is little understanding of how journalistic doxa might need to expand to keep up with technology. Ensuring ethical practice is becoming more critical in a polarized political climate where mis- and disinformation abound, audiences demand transparency, and the very boundaries and definitions of journalism are contested by both journalists and their audiences. Utilizing field theory, through interviews with journalists and analysis of published codes of ethics and existing literature, this article examines how Canadian newsrooms are using A.I., and whether ethical frameworks are adequately evolving alongside technology.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 it