Synergy for Sustainability in the Upcoming Telecommunications Revolution
Bibliographic record
Abstract
This chapter examines the merger of two cellular companies (MOBILINK and WARID) for sustainability in the telecommunication sector of Pakistan. During 2011-2013, WARID faced the news of the possible sales of the company due to falling revenues, constant poor network quality, and lower network coverage in rural areas. In 2014, all telecom players participated in the auction for 3G/4G licenses, but WARID did not participate due to its technology neutral license (TNL). Important decisions were taken in 2014 like launching of 4G/LTE services in major cities, US$500 million investment, increase of tower sites, opening of new regional sales offices. These decisions along with presence of TNL made WARID an attractive target for merger with MOBILINK. In 2016, the formal merger was finalized for benefits like synergies in CAPEX/OPEX, fastest 4G network, network reach to rural areas, roll-out of new services like the internet of things (IoT) and mobile banking. The merger proved successful. During the first quarter of 2017, the company generated PKR 38.7 billion in revenues, up from the same period a year before.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".