IMPLICATIONS OF COVID-19 LOCKDOWN POLICY ON SOCIO-ECONOMIC DEVELOPMENT OF NIGERIA
Bibliographic record
Abstract
The paper underscored the COVID-19 lockdown policy in Nigeria and its accompanying effects on socio-economic development of the country. The policy and its negative impacts on Nigerian Gross Domestic Product of second quarter, 2020 were also discussed extensively. Conceptual definitions of lockdown policy and socio-economic development were equally given. Implementation guidance for the lockdown policy was clearly stated in the paper. Conclusively, it was maintained in the work that the policy went a long way in reducing the number of persons that would have contracted the virus and also enabled the government to attend to those that were confirmed positive resulting to their quick recovery although with some deaths. The negative consequences of the policy were equally acknowledged in the paper. In view of the above, some recommendations were made which included the government setting up commission of inquiry to unravel the situations that resulted to the deaths of some Nigerians in the hands of security personnel during the lockdown policy and government developing urgently targeted economic empowerment strategy which can come in form of cash transfer program to mitigate the negative impact of the policy among others.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| 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".