The Knowledge of People About the Use of Renewable Energy and Environmental Awareness in Their Area, Irbid Governorate as a Case Study
Bibliographic record
Abstract
In the global effort to curb energy consumption and promote a sustainable lifestyle for our societies, we must strive to lower our energy needs in all aspects of our lives. One of the biggest contributors to our energy requirements are the buildings we spend most of our time inside. Buildings’ energy consumption can take many forms, such as, air conditioning, heating, ventilation, and lighting systems in order to create a comfortable environment for the users. One way of reducing buildings’ energy consumption is the use of renewable resource for energy. The main aim of this research is to measure and assess the public perceptions, knowledge and awareness of the concept of renewable energy, with specific regards to the use of solar photovoltaic cells, as well as investigate the desire to spend on the installation of renewable energy sources. Data was collected through a survey questionnaire applied in Irbid governorate in the north of Jordan. The statistical SPSS program was used to analyze closed-ended questionnaires and obtain numerical results based on arithmetical averages and percentages. The results show people are adequately aware of the benefits of renewable energy and most would like to have photovoltaic cells installed. However, 54.35% of the study sample live in apartments and do not have the space for the installation. 70.1% are open to the idea of sharing the solar energy system with their neighbors. 50% thought that the photovoltaic cells affected the aesthetics of the architecture style of the buildings especially the more traditional styles. It is concluded that the government needs to build a large-scale solar energy project to sustainably produce electricity instead of relying on individuals who generally lack the ability or the space for such systems, taking in note that the general public supports such concepts.
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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 | 0.001 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".