Enemmän vähemmällä : laman ja teknologisen murroksen vaikutukset suomalaisissa toimituksissa 2009-2010
Bibliographic record
Abstract
between journalist generations were connected with different practices and technologies that each generation adapted to and with which they acquired the profession.Generational thinking leads easily to stereotypical understanding of the skills and competencies of the individual journalists but it can also be applied to audiences.Most of the newsrooms were concerned over the loss of young audiences.The young were seen to predict the future of journalism and thus considered vital for the media.Young were equated with the Internet, social media and technological skills and therefore the online-publishing was seen as a key to reach the young.In this way subcultural capital, connected to participatory and online cultures, seems to be emerging in the journalistic field, blurring the boundaries of professional and amateur production.Journalists appeared rather unanimous of the need for quality journalism and that to produce quality means more time.The solutions realized in the newsrooms were however seen as taking the opposite direction: as news work becomes more fragmented, time to absorb oneself in the news topics decreases.Persistent and open-minded development, as well as public support of multiple journalisms was seen crucial for the future of quality journalism.Although one of the main ideas of the convergence culture lies in cumulating knowledge, this was not identified in the newsrooms, at least not in this research.Instead, reforms seemed to move away from expertise and it seems that the multiple resources in newsrooms were not made of use, at least not yet.The increased rush and fragmentation in the newsrooms also suggest that the prospects for critical, investigate journalism are weak.Moreover as the public sphere becomes increasingly fragmented, it is challenging to identify those public spaces where the decisive social and political debates take place. Sisällys
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.055 | 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".