Getting the Most Out of Known Unknowns: \nHow the Access to Information Act Impacts Journalistic Practice
Bibliographic record
Abstract
The Access to information Act (ATIA) is an essential yet inadequate piece of legislation that, in theory, helps to facilitate democratic engagement. Making use of this legislation is an essential way for journalists to hold power to account, to provide the public with newsworthy information, to illuminate government officials’ decision-making processes, to verify information gained from other sources and to provide context for their readers. \n \nUnfortunately, the challenges of navigating the ATIA pose significant setbacks for journalists. The most notable examples of these challenges include excessive delays, redactions, fees, and an inefficient complaints process. The inability to gain access to meaningful government information in a timely and cost-efficient manner deeply affects the quality of journalism that can be produced. \nThese practical challenges are combined with a financially strained news industry where fewer full-time journalists must accomplish more than their predecessors, with fewer available resources. There are multiple negative effects because of these issues: The ATIA is not being used to its fullest extent, the quality of journalism being produced is hampered by incomplete information, and the ability of citizens to make informed choices in the political sphere is obstructed. \n \nThis research addresses the lived experiences of journalists who navigate the ATIA as part of their journalistic practice. By drawing on original interviews, this thesis presents a thematic analysis of the most pressing issues that journalists face, as well as the most successful strategies that can be employed by journalists and the general public alike to gain access to government information.
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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".