Bibliographic record
Abstract
Putting the emphasis on the cost advantage and the apparent simplicity of these technologies, authors consider that social media represents a huge opportunity for SMEs.According to Barnes et al. (2012, 688) "many of the tools of Web 2.0 are cheap to acquire and operate, and require little technical expertise", what makes them particularly suitable for smaller businesses.Harris and Rae (2010) stated that social media will have a critical role in the survival of small firms and change the dimension of their competition with larger businesses.As a matter of fact, a growing number of SMEs are currently experiencing with social media.A study of Michaelidou et al. (2011) shows that most of them have the intention to increase their spending on social media.As a result, for many small businesses, social media has become their largest web presence, overtaking their corporate websites programmes (Neff, 2010).Research on the use of social media in a SME context has been growing since a couple of years.From this stream of literature, authors have investigated the uses small businesses are making of social media technologies and the benefits they could derive from such uses (
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".