Exploring the Image of Mary as Bridge-Builder (Pontifex) for Contemporary Contextual Theology
Bibliographic record
Abstract
In this dissertation I propose that the image of Mary as bridge-builder (Pontifex) is a relevant model of inculturation for Canadian-born Chinese Roman Catholic women (CBC-RC women). First, I establish the insufficiencies in both the popular image of Mary as mother and existing ethnic depictions of Mary, such as Our Lady of La Vang and Our Lady of China/Donglu. This is done through looking at the works of feminist theologians and “inculturationist” theologians, respectively. While the first investigation reveals patriarchy and gender essentialism as key contributors to the unrelatability of Mary by groups of women more generally, the latter exploration affirms the need for religious teachings and figures, such as Mary, to be fully immersed in the local culture. If the image of Mary is not fully reflective of the culture of the local women, she cannot fully understand their sufferings and provide helpful solutions. I present the image of Mary as Pontifex to the reader by examining the different ways Mary acts as a bridge-builder in both the Gospel narratives and in Roman Catholic tradition. Mary, as an advocate for humanity, bridges between humanity and the divine, and as a mediator of God’s Will and Word, she bridges between the divine and humanity. Drawing on linguistic and sociological works on child-brokering (children who translate and interpret language and culture for their immigrant parents), I demonstrate how CBC-RC women as child-brokers also participate in bridge-building as mediators and advocates, not unlike Mary as Pontifex. Mary as Pontifex can become an inculturated model for CBC-RC women because she and CBC-RC women participate in bridge-building and the “both-and” culture, and Mary as Pontifex can address CBC-RC women’s experiences of intersecting systems of oppression.
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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 | 0.010 | 0.048 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".