Economic impacts and effects on communities of the CSG industry in Queensland
Bibliographic record
Abstract
Social licence to operate is a key issue in the eastern Australian gas market as it transitions to liquefied natural gas (LNG) exporting and relies on unconventional gas to satisfy this new demand. Although there is a large body of research on the environmental, social and economic effects attributable to unconventional gas activities, more knowledge is needed about the economic impacts of the coal seam gas (CSG) industry and the effects of the various stages in the CSG value chain experienced by communities. The Department of Industry has undertaken a study on Queensland’s experience with CSG development. A synthesis of existing economic impact studies relating to the CSG industry in Queensland finds that while there are economic benefits, a greater understanding of how the benefits and costs are spread among and in communities is needed. It also finds that there is little knowledge of the cumulative impacts of multiple concurrent projects in addition to the impacts of existing land usage. An assessment of effects from CSG activities that may directly or indirectly affect the economic welfare of communities in the Bowen and Surat basins highlights that while health impacts, land access and usage, water impacts, transport nuisance and noise pollution are all perceived to be significant, community perceptions about these effects change in time along with changes in the nature and scale of underlying activities. Opportunities for specific economic analysis on specific CSG activities and their associated consequences are also identified in this extended abstract, which may assist in addressing existing information and regulatory gaps.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".