The Socio-economic Effects Of Covid-19 Lockdown in Nigeria: Implications on Micro and Macro Economy
Bibliographic record
Abstract
Many countries across the planet are facing unprecedented challenges as a result of COVID-19 infections. Nigeria, Africa's most populous country is no exception. The government has implemented a range of measures to curb the spread of the pandemic, including closure of international airports, shutting down of institutions, markets/stores etc. On March 29th, an initial four-week state-wide lockdown was declared in three major states, Lagos, Abuja and Ogun, halting all essential activities. Following this Executive Order, state governments throughout the country took stringent measures such as restrictions on inter-state travel, instituting curfews, etc. Against this backdrop, the paper reviewed the socio-economic effects of COVID-19 lockdown in Nigeria and its implications on the micro and macro economy. The study adopted the systems theory. Due to safety protocols established by health experts on the COVID-19 pandemic, data for the study were drawn from participant observation, media commentaries and authentic secondary sources. The content analytical technique was used to review the literature on the subject matter. The study reported that the halt in business activities in the country has rendered many penniless and unable to provide for themselves the basic amenities needed for the duration of the lockdown. The study concluded that Federal Government of Nigeria should waive payments on personal and corporate income tax for the second quarter and third quarter of 2020, considering that the shock has affected the income and profits of households and businesses.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 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".