Journal of Forest Business Research: a leading platform for advancing forest business and investment science research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Journal of Forest Business Research (JFBR), an international peer-reviewed and open-access journal, has been developed to offer a novel publication avenue for forest business research contributions. This effort has been motivated by the realization that there were no dedicated forest business scientific journals in existence and the need to have a scientific journal to support growing volume of forest business research. The journal aims to effectively meet the needs of contributors and readers by bringing together academic and professional business research in forestry. The following section describes why there is a need for the JFBR and what makes this journal a leading platform for advancing forest business and investment science research. Then, we summarize all the papers included in our two issues in 2023. This year, we delivered to hands of our readers over 340 pages of high-quality forest business and investment science research. The articles published in 2023 discussed, among others, forest carbon and its contribution to total timberland investment returns, capital investment and annual expenditures related to forests in the United States (U.S.), wood pellet manufacturing industry from residents’ perspectives in the U.S. South, discount rates in forest management decisions, the effect of various COVID-19 policies on standing timber prices in the U.S. South, the relationships between innovation constructs and demographic and management attributes of wood furniture firms in Kenya, the economic feasibility of silviculture investments to reduce butt rot and ungulate browse damage in Canada, the sustainability of the production, processing, and exporting systems of frankincense (Boswellia papyrifera) in Ethiopia, and the development of the Iranian wood products industry over the past two decades. All these articles truly show the international character of forest business research. In the final section, we indicate what types of articles we are seeking and how you can support our efforts.
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.
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 | 0.046 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.025 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| 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 it