Bibliographic record
Abstract
Introduction I wrote the first draft of this chapter in the same that week the colonial (federal Canadian) government announced its first budget since the onset of the global coronavirus (COVID-19) pandemic in early 2020. Delivered by the first woman finance minister (and deputy prime minister), the budget was characterized by the government as ‘very much a feminist plan’ (Government of Canada, 2021). Two key foci were national investments in childcare and national standards for long-term care (institutional seniors’ care), both dimensions of the ‘crisis of care’ intensified (though by no means instigated) by the pandemic (The Economist, 2021). These key policy commitments appeared to reverse decades of state-led divestment, marketization and (re)privatization of services to support care and social reproduction, researched and theorized by feminist scholars, including feminist economic and labour geographers (see, for example, Bakker and Silvey, 2008; Molinari and Pratt, 2021; Schwiter et al, 2018a). They were precipitated by evidence in Canada and elsewhere that the economic impacts of the pandemic are gendered, and that both unemployment and the increased burden of unpaid labour have been disproportionately borne by feminized workers – impacts that will not have surprised feminist scholars of structural adjustment or the 2008 global financial crisis and austerity regimes in Europe. Pandemic-related unemployment and impacts on livelihoods are also racialized and classed, shaped by White supremacy, colonialism and imperialism (Krupar and Sadural, 2022; Neely and Lopez, 2022). The current pandemic moment thus represents an intensification of trends that feminist economic geographers have long signalled (Nagar et al, 2002; McDowell, 2003; Mullings, 2005; Pollard, 2013), and has pulled back the curtain on the household as a domain of paid and unpaid work invisibilized or ignored in economic research (Ruwanpura, 2013; Pimlott-Wilson, 2015; Worth, 2018). The economic geographies of our present conjuncture are highly uneven, seemingly unprecedented, yet rooted in historical socio-spatial structures, processes and institutions of production and reproduction that shape the landscapes of racialized global capitalism today. They spur us to examine how feminists have long signposted an agenda for economic geography that understands economic development and crisis in relation to these socio-spatial relations and their exclusions, and seeks to ground economic geography's future in a more inclusive and politicized vision of the economy and understanding of who counts within it.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
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".