Bibliographic record
Abstract
Abstract Natural hazards such as floods, droughts, and earthquakes do not discriminate, but individuals of varying gender identities are impacted by, experience, understand, and respond differently to disasters. Research on gender in disaster contexts first began in the 1990s and grew to examine topics including gendered vulnerabilities, capacities, women’s rights, and representation. This was bolstered by the rise of global women’s movements and the institutional recognition by international relief agencies and the United Nations of women’s needs and participation in disasters. In addition to the growth of various feminist movements, feminist scholarship in academia challenged the predominance of positivist epistemologies, quantitative methodologies, and male bias in the gathering, analysis, and presentation of data in disaster research. Feminist scholarship aided in the shift in disaster studies from a hazards paradigm to a vulnerability paradigm wherein the study of disasters is no longer confined to the measurement and management of physical forces but also includes the uncovering of the political processes that produce disasters. Feminist scholars began to promote the critical use of self-reflexive, in-depth qualitative methodologies such as ethnography, participatory action research, and activist collaborations with grassroots civic organizations. Such research studies examine power relations and inequalities, and they strive toward realizing emancipatory goals for social justice in the fields of disaster research and practice. Critical disaster research continues to advance in the early 21st century through the persistent questioning of the “natural”-ness of disasters. Despite the great strides in gender studies in disasters, the word “gender” remains predominantly equated with the category of heterosexual women and therefore perpetuates the male–female and nature–culture divides inherent in the Western epistemologies that underlie disaster research. Therefore, scholars who employ postcolonial, antiracist, and decolonial feminist frameworks trouble the coloniality of disasters, theorize, and study the violence of the colonial present on gendered and racialized spaces and bodies. Creative arts-based and participatory methods, including oral histories, photovoice, interviews, theater, body mapping, among others, are used to make visible those who are misrepresented and absent in disaster discourse. Gender and sexual minorities have also been historically neglected in disaster research, and the advancement of queer scholarship has begun to make more visible the lives of non-heterosexual identities in disasters. The conduct of fieldwork, interviews, ethnography, autoethnography, and collaborative and even quantitative methods can be queered or made non-normative through the examination of intimacies, subjectivities, emotions, performativity, relationships, and ethics in gender research. Last, the rise of climate change adaptation studies, policies, and practices also presents similar gaps in gender research. Feminist research methods such as the use of participatory geographic information system mapping challenge technological assessments of climate change adaptation interventions. They aid instead in sustaining a political analysis of power, examining people’s susceptibility to harm, together with processes that maintain this exposure to danger for bodies of different gender identities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".