The efficiency paradox: A temporal lens into online dating among Chinese immigrants in Canada
Bibliographic record
Abstract
Online dating is widely assumed to enhance the overall efficiency of relationship formation through expanding the pool of potential partners. Yet little is known about how this presumed efficiency plays out beyond the initial search stage. Although temporal compression (i.e., saving time) is considered central to the notion of efficiency, individuals' lived realities of time and efficiency in online dating remain understudied. Adopting a grounded theory approach to analyzing 31 in-depth interviews with heterosexual Chinese immigrant online daters in Canada, we reveal how time-related expectations and experiences shaped their perceptions of (in)efficiency throughout different stages of online dating. Specifically, our participants started with an efficiency expectation of temporal compression, expecting online dating to save time. As the dating process unfolded, however, they experienced inefficiency through diverse temporalities, including temporal suspension and simultaneity in mediated communication and temporal reconfiguration during modality switching. These experiences contradicted our participants' initial efficiency expectation, prompting some to reevaluate their expectation and develop a preference for temporal slowdown in dating. Our findings highlight an "efficiency paradox" whereby the promise of efficiency not only runs counter to online daters' lived realities but also amplifies perceptions of inefficiency. Foregrounding the voices of racial minority immigrants, our study challenges the commonly envisioned efficiency of online dating and provides new insights into how digital technologies mediate intimate lives through shaping individuals' temporal experiences.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".