Escaping Conformity : Hur småskaliga företag bedriver kommunikationsarbete
Bibliographic record
Abstract
This thesis explores how small-scale businesses in Stockholm and Uppsala handle communicative work, with escape rooms as the example investigated. Interviews are conducted with employees managing communicative tasks. Areas of analysis are branding and authoring (as per the Montreal school of communication, in the CCO perspective on organizations). Due to the fact that small-scale businesses are underrepresented in previous research in the field of organization communication, this essay aims to provide further findings and expand upon the research in the field. Moreover, as CCO perspectives, and the Montreal school in particular, are mainly adapted to research on large-scale organizations, this essay evaluates how well it can be used to analyze smaller organizations. The findings show that reported authoring within the companies varies, as due to company size as well as position of the representative interviewed. Further, the extent to which branding is used as a strategy within the organizations varies from virtually no use, to considerable integration internally as well as externally. All interviewees express that the communicative work within their respective companies is as of yet underdeveloped, and requires more work to reach satisfactory capacity.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".