Bibliographic record
Abstract
This paper reconceptualises the role of the small “local” newspaper in a new media environment and argues that definitions and concepts currently used to describe and define such publications are becoming increasingly problematic as newspapers shift into both print and online formats. The paper highlights the continued importance of geography for such newspapers at a time when there is wide academic debate on the relevance of territory and boundaries and the impact of time–space compression in a new media world. It argues, however, that a focus on a newspaper’s geographic connection must also acknowledge the increasing boundlessness and openness of the social space in which a newspaper operates. Ultimately this paper suggests the concept of “geo-social” news may be a more appropriate framework for scholars to consider such publications. I draw on the work of geography scholars, and discussions around “space” and “place” to construct the notion of “geo-social” news, highlighting some exemplars of small commercial newsroom practices in Australia, the United Kingdom and Canada and discussions with newspaper editors in Australia to demonstrate the relevance of the “geo-social” concept.
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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.016 |
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".