Forestry Ergonomics and Occupational Safety in High Ranking Scientific Journals from 2005–2016
Bibliographic record
Abstract
The occupational safety and health change through time due to technological and social development. It is an obligation of scientific research to impartially and critically examine these changes and propose measures to reduce negative impacts on people. Since the forestry as an industry sector follows general changes, we tried to establish the situation in the field of occupational safety and health in forestry by reviewing the studies in the period 2005–2016. The review included studies, the results of which have been published particularly in scientific journals relating to the field of forestry and ergonomics with an impact factor. The findings show that the number of published articles in the field of occupational safety and health and ergonomics increases. Studies were mostly limited to only three continents, namely Europe and North and South America, and 26 countries in total. The majority of research was conducted in Canada, Brazil and Sweden. The largest number of research relates to traditional technologies of harvesting (chainsaw and skidder), whereas the Nordic states prevail in terms of modern, mechanized technologies. The study shows that international and intercontinental cooperation of researchers must be further stimulated in the field of research and education. It has been identified that there is a lack of studies addressing the issue of biomass production, forest road and skid trail construction, and some new technologies. There is a deficiency of cognitive studies, studies of workers’ burnout and comprehensive studies of ergonomics and productivity in the field of ergonomics. The uniform statistics of recording accidents will provide the research to be conducted in all forestry operations and enable the preparation of efficient preventive measures.
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 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.077 | 0.069 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".