Shades of green: linking environmental locus of control and pro‐environmental behaviors
Bibliographic record
Abstract
Purpose The purpose of this research was to examine the impact of various attitudes and personality characteristics on environmentally‐friendly behaviors, from a locus of control (LOC) perspective. Specifically, we developed and tested a model linking a related construct, environmental locus of control (ELOC), to a series of pro‐environmental behaviors. Design/methodology/approach The context related to various personal and household behaviors vis‐à‐vis the environment, and the subject pool consisted of a diverse group of urban consumers. A survey was employed to measure various attitudinal and personality variables corresponding to internal/external locus of control, as well as a battery of pro‐environmental behaviors. The research propositions were tested using a structural equation modeling approach. Findings We found four distinct dimensions of ELOC, two of which relate to an external LOC (“biospheric‐altruism” and “corporate skepticism”) and the other two relate to an internal LOC (“economic motivation” and “individual recycling efforts”). We then linked these four dimensions to a variety of pro‐environmental behaviors. Highly variable patterns were obtained, with different dimensions assuming a greater or lesser impact, or no role at all, depending on the specific behavior under analysis. Research limitations/implications Generalizability of the findings is limited due to the sample (urban consumers from one major city), and the method employed (validity of self‐report measures and the non‐experimental nature of the field study). Practical implications Our findings highlight the importance of considering the specificity of pro‐environmental behaviors, when assessing the antecedent roles of pro‐environmental attitudes/dispositions, which are in‐and‐of‐themselves, complex and multidimensional. Originality/value In this era of environmental degradation, researchers, managers, and public policy makers alike need to consider that pro‐environmental attitudes are composed of multiple dispositional facets, and that the role of these facets is highly context‐specific.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".