Fair governance and Islamoexploria: the interaction of government administrators and the marginalized
Bibliographic record
Abstract
This study addresses the concept of fair governance based on an empirical study with marginalized groups, primarily Muslims, and their interaction with government agencies as its salient locus of investigation. Employing the research method of in-depth interviewing, I present a qualitative analysis of 35 semi-structured interviews with Muslims and government administrators. The methodological framework based on which these interviews are interpreted is rooted in the tradition of social constructivism as manifested in the grounded theory perspective of Charmaz. My examination of the hitherto unspoken political visions of the study participants and their shared perspectives offers pragmatic solutions to create greater equity and fairer inclusion of the marginalized in civic and political dialogues and in the administrative practice of government. Remarkably, the cultural changes towards justice and inclusion in the Government of British Columbia manifest that fair government is committed to creating a fundamental transformation in favour of marginalized groups. I find the most promising approach for such transformation occurs where bottom up and dynamic approaches of civil society are aligned with top down approaches of government to justice. The findings suggest that fair governance enhances its functionality and capacity through reflecting universal universalism in its policies and practices, heartening public spirituality and moving towards a more humane modernity rather than the extant western model of modernity. Thus, fair governance calls for diversity in expression of religious identity and challenges the mistaken images of Muslim women. Subsequently, fair government welcomes female religious actors, who act upon religious values, to its administration and respects their choice of clothing encompassing the scarf. Fair government, at all levels, ameliorates the ethical standards of its employees and employs authentic leaders, who act in a virtuous manner, care about employees’ deeply held values, and implement direct communication with staff. Such government supports legislative and constitutional reforms to consider a different outlook of the marginalized on political and social concerns, respects religious practices, honours Muslims’ identity and interpretation of life, and supports individuals who aim to improve humanity in Canada and its occupational settings. Rethinking Islamophobia in the context of the distinct need of government administrators for the institutional education about Islam, as a key finding of the study, depicts the emergence of “Islamoexploria”, as a new expression, which I coin. In my study, there is ample evidence to suggest that a sample of government administrators in British Columbia is in the age of post Islamophobia since they, as pioneers, have passed the stage of Islamophobia and entered a new era of “Islamoexploria”. Thus, they have produced the profound socio-cultural changes towards understanding Islam by shifting from fear of, ostensibly, the unknown to knowledge about the unknown and to approaches that are more sympathetic to Muslims. This finding suggests that fair government facilitates the journey from western Islamophobia, a demonstration of old racism, to “Islamoexploria”, a contemporary thirst for knowledge about Islam. Concurrently, Muslims remain responsible to contribute to fairness at large by role modeling their religious values, which greatly promote justice, compassionate attitudes, and humanitarian actions.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.029 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| 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".