Modelling for policy assessment in the electricity supply sector of Pakistan
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
Purpose The purpose of this paper is to provide a long‐term assessment of Pakistan's electricity policy in the context of both environmental and resource constraints. To increase the sustainability of energy supply, the Government of Pakistan introduced a series of reforms in the electricity supply sector during 1990‐1995. In response to these policy incentives, most of the independent power producer offers included coal, oil, and/or gas‐based power plants. Considering that Pakistan produces only up to 40 percent of its oil demand domestically and thermal power generation causes CO 2 emissions, there is a great need for an assessment of the existing electricity policy. Design/methodology/approach Drawing on system dynamics methodology, this study presents and utilizes a dynamic simulation model that captures the dynamics of the sectors underlying the electricity supply system including investments, capital, production, resources, financial resources, and the environment. Findings The key findings of this study are: policy incentives encouraged thermal‐based generation at the potential expense of hydro power generation; and the evolution of electricity supply related CO 2 emissions exhibits an exponential growth. Research limitations/implications While there are other emissions related to the electricity supply system with potentially severe environmental concerns, for example SO 2 , this study focuses only on CO 2 emissions. Originality/value The paper offers a system dynamics model and provides some useful policy insights for the electricity supply sector of Pakistan.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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