Changing objectives of non-industrial private forest ownership: a confirmatory approach to measurement model testing
Bibliographic record
Abstract
While the behavior and objectives of non-industrial private forest (NIPF) owners have been studied extensively, studies that systematically test the underlying measurement model are lacking in forest economic literature. Our paper reports the results obtained from a recent large-scale survey conducted in Finland in 2011 (n = 557). Results indicate a novel way to systematically analyze the objectives of forest ownership by testing the validity of the developed measurement scale using the structural equations modeling technique. From an exploratory factor analysis of 22 items measuring forest owner objectives, a four-dimensional structure is identified in the background objectives of NIPF owners. These dimensions are labeled as recreation and leisure time, sense of economic security, nature conservation and aesthetics, and timber sales income objective. Having undergone a confirmatory testing process, results from the four-dimensional model support the validity of the developed 16-item measurement model. Based on these findings, we argue that the logical NIPF owner objective structure in Finland consists of experiential forest value, as perceived in current and future time contexts, as well as of current and future economic objectives. As the theoretical structure divides forest owner objectives into the evaluation of the present objectives, supplemented with a psychological evaluation of the future objectives, a novel classification of NIPF owner objectives is suggested.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".