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- เผยแพร่เมื่อ 30 มิ.ย. 2024
- Creating a fair, non-biased scholarship selection framework is essential. Reviewr employs several strategies to ensure fairness and objectivity:
-Randomized Review Assignments: Reviewr can randomly assign applications to reviewers. This method helps prevent any preconceived notions or biases that reviewers might have towards certain candidates, promoting a more equitable evaluation process. There are many ways to structure a review and selection workflow that can still rely on a form of randomization, if if a workflow consists of phases, committees, categories, etc.
They key component to randomization of the submission to evaluator pairing is to first identify the workload capacity of reviewers and then from here, identify how many times each individual submitter must be reviewed to get a proper gauge on the quality of the application. For example, we may decide that review teams should not evaluate more than 20 people due to time constraints, but at the same time, each applicant must get reviewed by 5 different evaluators. Within Reviewr, we can just enter these metrics and the system will auto generate the assignments.
-Anonymization of Submissions: To further prevent bias, Reviewr can redact any identifying information from applications. This ensures that evaluations are based solely on the merits of the content and the qualifications of the candidates, not on any personal or demographic characteristics. Any information that is also not relevant to the review and selection process such as data collected for record keeping purposes, even if not PII, should also be redacted to lower the barrier for the selection team and ensure a seamless experience.
-Transparency in Processes: The organization provides clear guidelines and criteria for evaluations, which are openly communicated to all participants. This transparency helps build trust in the fairness of the process and ensures that all candidates understand how decisions are made.
Incorporation of Diverse Evaluation Metrics
-Beyond Academics and Professional Achievements: Criteria now include evaluations of leadership qualities, community involvement, innovative thinking, and resilience, among others.
-Cultural and Contextual Relevance: Adjusting criteria to reflect the specific cultural, social, and economic contexts of applicants, recognizing that excellence and potential can be conveyed differently across different settings.
Customized Weighting of Criteria
-Flexible Weighting System: Criteria can be weighted differently depending on their relevance to the specific goals of the program.
-Adaptation: The criteria and their weightings are regularly reviewed and adapted based on feedback from stakeholders and evolving program goals.
Scoring Models
-Holistic Scoring: Instead of strict numerical scoring, a more narrative-based evaluation may be used to capture the nuances of each candidate’s contributions and potential impacts.
-Feedback-Driven Improvements: Ongoing adjustments to scoring models based on evaluator feedback and participant outcomes help ensure that the evaluation process remains relevant and effective.
