Mapping Nollywood’s Imaginative Scape in Canada: Understanding Transnational Nigerian Media, Identity and Belonging.
Bibliographic record
Abstract
Recent years have seen increasing scholarly recognition of transnational Nigerian cinema (“Nollywood”) as an important tool of cultural representation, and a conduit of diasporic communication. Nollywood plays a central role in shaping understandings of Nigerian culture, identity, and society in transnational spaces. Despite this growing scholarly awareness, there is a paucity of empirical research into how diasporic Nigerians spread across time and space receive and interpret Nollywood media texts. This study addresses the gap by examining the ways in which Nollywood shapes global understandings of Nigerian culture, identity and society, and the sociocultural implications. \n \nThis dissertation is a qualitative analysis of the significance of Nollywood through the lens of diasporic Nigerians in Montreal, Quebec, Canada. Through participant observation and one-on-one interviews, I map out the ways diasporic Nigerians utilize Nollywood film culture to negotiate and sustain ethnocultural identity and develop a sense of belonging in Canadian society. The goal is to clarify the significance of Nollywood, and thereby deepen understanding of the ways in which Nollywood can be utilized to promote dialogue on critical issues of race and representation in the Canadian and Quebecois contexts, but also within the diasporic world in general. \n \nI draw on Stuart Hall’s encoding and decoding model of communication (Hall 1980), within the broader framework of media uses and gratification theory (Blumer and Katz 1974) and dependency theory (Ball-Rokeach and DeFleur 1976), to interrogate the way participants make meaning with Nollywood media texts in context. The conceptual framework is therefore communication and media studies, transnational cultural studies, postcolonial studies, migration and diaspora studies, and cultural anthropology. \n \nI use this research to examine the premise that Nollywood is an important phenomenon of representation and a conduit of diasporic communication in contemporary times. I argue that scholarly analyses that tend to focus more on Nollywood’s material culture and infrastructure, and less on ethical and ideological frameworks have misrepresented the media’s cultural significance. The significance of Nollywood can only be accurately understood by looking beyond its medium specificity to the cultural systems and ideologies involved.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.030 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".