Employing the Social Media and the Mobile Phones (GSM) in the Campaign Against Open Defecation in South-East Nigeria
Bibliographic record
Abstract
This exploratory study investigated the viability of using the social media and mobile phone (GSM) as public relations social marketing tool in the campaign against open defecation in South-East Nigeria. It argues that the greater percentage of the public could be reached with the campaign if approached through the social media networks and GSM such as the Facebook, mobile telephone, etc., than the traditional media of newspapers, radio and television that have not yielded much in the envisaged awareness and attitudinal change results. From a survey sample of 385 respondents drawn from three sampled states of Enugu, Anambra and Abia, using the simple random, convenience and purposive sampling techniques, the results suggest, among others, that the social media and the GSM could be more efficacious in prosecuting the campaign against open defecation given the fast growing social media literacy and GSM use among the population especially the youths. It recommends that given the increasing number of the segment of the society especially the youths that use the Social Media and GSM the South-East governments could conduct basic or pilot study so as to leverage on this accessibility aspect of the media for a more effective campaign to end open defecation in South-East Nigeria.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".