Jargon as a Status Compensation Mechanism

Table of Contents

Overall Summary

Overview

This research investigates the relationship between social status and jargon use, proposing that individuals with lower status utilize jargon to compensate and signal higher status. Nine studies, employing archival data analysis and experiments, explore this proposition across various contexts, including academic dissertations, business pitches, and live conversations. The research suggests that this behavior is driven by a heightened concern with audience evaluation rather than communication clarity.

Key Findings

Strengths

Areas for Improvement

Significant Elements

Figure 1

Description: Visually summarizes the key findings across multiple studies, demonstrating the consistent pattern of increased jargon use by low-status individuals in various contexts.

Relevance: Provides compelling visual evidence supporting the central hypothesis of the paper.

Figures 2 & 3

Description: Path diagrams illustrating the mediating role of evaluative concern in the relationship between status and jargon use (including legalese).

Relevance: Visually depict the mediating mechanism, demonstrating how low status leads to increased evaluative concern, which in turn drives jargon use.

Conclusion

This research establishes a novel link between social status and jargon use, demonstrating that lower-status individuals utilize jargon as a form of compensatory conspicuous communication. The findings contribute to our understanding of how status dynamics influence communication strategies and highlight the role of evaluative concern in driving this behavior. Further research exploring moderators, long-term consequences, and potential interventions could provide a more comprehensive understanding of this phenomenon and its implications for social interaction.

Section Analysis

Abstract

Overview

This abstract summarizes a research paper exploring the relationship between jargon use and social status. It proposes that jargon serves as a status compensation mechanism, where individuals with lower status use more jargon to signal higher status. Nine studies, including archival data analysis and experiments, support this proposition, finding a correlation between lower status and increased jargon use across various contexts like academic dissertations, business pitches, and live conversations. The research suggests that this effect is driven by increased concern with audience evaluations.

Key Aspects

Strengths

Suggestions for Improvement

Introduction

Overview

This introduction sets the stage for research on jargon use as a status compensation strategy. It defines jargon, differentiating it from slang and technical terms, and outlines its communicative and signaling functions. The authors hypothesize that low-status individuals use more jargon to signal higher status, driven by a concern for audience evaluation.

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Table 1

Table 1, titled 'Definitional distinctions between Slang, Jargon, and Technical Terms,' compares these three language forms across four dimensions: Permanence, Learning process, Context of use, and Formality. It highlights that jargon occupies a middle ground, being faddish like slang but used in professional contexts with more formality, unlike slang's informal social use. Technical terms are enduring, learned asocially, and used in professional, formal settings.

First Mention

Text: "Overall jargon occupies a middle ground between the rich social functions that slang performs and the more formal and precise functions that technical terminology offers (see Table 1)."

Context: This mention occurs at the end of section 1.1, 'Definition of jargon,' after differentiating jargon from slang and technical terms. The sentence directs the reader to Table 1 for a clear comparison of the three language forms.

Relevance: This table is crucial for clarifying the definition of jargon, a central concept in the introduction and the overall study. It distinguishes jargon from related terms, establishing its unique characteristics and justifying its use as a focus of research.

Critique
Visual Aspects
  • The table's simple structure, with clear row and column headings, makes it easy to compare the three language forms across the four dimensions.
  • The use of concise descriptive terms (e.g., 'Faddish,' 'Social,' 'Formal') enhances clarity and avoids ambiguity.
  • The table could benefit from visual cues, like shading or borders, to further separate the rows and columns.
Analytical Aspects
  • The table effectively summarizes the key distinctions between slang, jargon, and technical terms, supporting the authors' definition of jargon.
  • The four dimensions chosen for comparison are relevant and capture important aspects of language use.
  • The table could be strengthened by providing examples of each language form within each dimension to illustrate the distinctions more concretely.
Numeric Data

Study 1a: Status as a predictor of jargon use in dissertation and master’s thesis titles

Overview

Study 1a investigates the relationship between author status and jargon use in dissertation and thesis titles. Using a dataset of over 64,000 titles from universities ranked by US News and World Reports, the study found a positive correlation between lower university status and increased jargon use, measured by linguistic complexity. This suggests that authors from lower-ranked schools compensate for their perceived lower status by using more jargon.

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Table 2

Table 2, titled 'Descriptive statistics and correlations for variables used in Studies 1a and 1b,' presents descriptive statistics (mean and standard deviation) and correlations for five variables: Readability Jargon Measure, Acronym Jargon Measure (Yes/No), Status Rank, Number of Pages, and a binary variable for the year 2016. The table shows a mean of 87.21 (SD = 58.01) for the readability measure, a status rank mean of 0.30 (SD = 0.76), and a mean number of pages of 157.14 (SD = 95.78). The correlation between readability and status rank is -0.0009, while the correlation between acronym use and status rank is 0.028.

First Mention

Text: "Table 2 presents descriptive statistics for and correlations among the variables in Study 1a (and Study 1b)."

Context: This mention appears in the 'Results and Discussion' subsection of Study 1a, right before the presentation of the main regression results. It introduces the table that provides an overview of the variables used in both Study 1a and 1b.

Relevance: Table 2 provides context for the regression analysis presented in Study 1a by showing the descriptive statistics and correlations of the key variables. This helps readers understand the nature of the data and the relationships between variables before interpreting the regression results.

Critique
Visual Aspects
  • The table is well-organized, with clear labels for each variable and statistic.
  • The use of standard abbreviations (M, SD) for mean and standard deviation is appropriate.
  • The table could be improved by visually separating the descriptive statistics from the correlations, perhaps with a line or different shading.
Analytical Aspects
  • The inclusion of both descriptive statistics and correlations provides a comprehensive overview of the variables.
  • The table would be stronger if it included information about the sample size for each variable.
  • The table could benefit from a brief explanation of the coding used for the 'Acronym Jargon Measure' and 'Year 2016' variables.
Numeric Data
  • Mean Readability Jargon Measure: 87.21
  • SD Readability Jargon Measure: 58.01
  • Mean Status Rank: 0.3
  • SD Status Rank: 0.76
  • Correlation between Readability and Status Rank: -0.0009
Table 3

Table 3, 'Regression results for Studies 1a and 1b,' presents the regression results examining the relationship between school ranking and jargon use (readability and acronym use) in dissertation/thesis titles. The table is split into two sections, one for each study, with two models each. Model 2 in Study 1a shows a coefficient of 0.00066 (SE = 0.00005, p < 0.001) for the 'Ranking of Author's School' variable when predicting readability, suggesting a positive relationship between school ranking and readability. Model 2 in Study 1b shows a coefficient of 0.00084 (SE = 0.00025, p < 0.001) for school ranking when predicting acronym use.

First Mention

Text: "Table 3 includes our primary regression results"

Context: This mention is in the 'Results and Discussion' subsection of Study 1a, immediately following the mention of Table 2. It indicates that Table 3 contains the main findings of the regression analyses.

Relevance: Table 3 presents the core findings of Studies 1a and 1b, directly testing the hypothesis that lower-status schools (higher ranking number) use more jargon. The regression results provide evidence for this hypothesis, showing a positive relationship between school ranking and jargon use.

Critique
Visual Aspects
  • The table is clearly structured, separating the results for each study and model.
  • The use of abbreviations (Coeff., SE) is standard, but defining them in a footnote would improve clarity for a broader audience.
  • The table's layout could be improved by aligning the decimal points in the coefficient and standard error columns.
Analytical Aspects
  • The table clearly presents the coefficients and standard errors for the key independent variable, 'Ranking of Author's School.'
  • The inclusion of control variables in Model 2 for each study strengthens the analysis.
  • The table would be more informative if it included standardized coefficients (beta weights) to allow for comparison of effect sizes across different variables.
Numeric Data
  • Study 1a, Model 2: Coefficient for School Ranking (Readability): 0.00066
  • Study 1a, Model 2: SE for School Ranking (Readability): 5e-05
  • Study 1b, Model 2: Coefficient for School Ranking (Acronym Use): 0.00084
  • Study 1b, Model 2: SE for School Ranking (Acronym Use): 0.00025
Table 4

Table 4, 'Sensitivity analyses for Study 1a,' presents the results of sensitivity analyses conducted to assess the robustness of the findings regarding the relationship between school ranking and readability. The table includes results for different sample restrictions (Top 200, 150, 100, and 50 schools). For instance, in the Top 50 schools sample (Model 8), the coefficient for 'Ranking of Author's School' is 0.00294 (SE = 0.00034, p < 0.001), indicating a stronger positive relationship between school ranking and readability in this restricted sample.

First Mention

Text: "Table 4 includes sensitivity analyses."

Context: This mention appears in the 'Results and Discussion' subsection of Study 1a, after the presentation of the main regression results in Table 3. It introduces the table containing the sensitivity analyses.

Relevance: Table 4 is important for demonstrating the robustness of the findings in Study 1a. By showing that the relationship between school ranking and readability holds across different sample restrictions, it strengthens the conclusion that the effect is not driven by outliers or specific subsets of the data.

Critique
Visual Aspects
  • The table is organized by sample restriction, making it easy to compare the results across different samples.
  • The consistent use of labels and abbreviations across tables (2, 3, and 4) improves readability.
  • The table could benefit from highlighting the key coefficient for school ranking in each model, perhaps with bolding or shading.
Analytical Aspects
  • The inclusion of both models with and without control variables for each sample restriction provides a comprehensive assessment of the effect.
  • The sensitivity analyses address potential concerns about the generalizability of the findings.
  • The table could be enhanced by including a brief explanation of why these specific sample restrictions were chosen.
Numeric Data
  • Top 200 Schools, Model 2: Coefficient for School Ranking: 0.00071
  • Top 150 Schools, Model 2: Coefficient for School Ranking: 0.00079
  • Top 100 Schools, Model 2: Coefficient for School Ranking: 0.00131
  • Top 50 Schools, Model 2: Coefficient for School Ranking: 0.00294

Study 1b: Status as a predictor of acronym use in dissertation and Master’s thesis titles

Overview

Study 1b examines the relationship between author status and the use of acronyms in dissertation and thesis titles. Using the same dataset as Study 1a, this study found that authors from lower-status schools were more likely to include acronyms in their titles, suggesting another form of jargon use as status compensation.

Key Aspects

Strengths

Suggestions for Improvement

Study 2a: Causal evidence that low status increases jargon use

Overview

Study 2a provides causal evidence for the hypothesis that low status increases jargon use. Participants, MBA students, were placed in a simulated startup pitch competition and assigned to different status conditions (lower, same, or higher status). They then chose between a high-jargon and low-jargon pitch description. Results showed that lower-status participants were more likely to select the high-jargon pitch.

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Figure 1

Figure 1, titled 'Use of jargon by status condition across experiments,' displays four bar charts illustrating the relationship between status and jargon use across multiple studies (2a, 2b, 3a, 3b, 4a, 4b, and 2c). Each chart compares low-status and high-status conditions, showing the percentage of participants selecting high-jargon options or the number of jargon terms used. The figure consistently demonstrates that low-status participants tend to use more jargon than high-status participants across different contexts, such as pitch selection, title selection, and conversational jargon use. For example, in Study 2a, approximately 41% of low-status participants selected the high-jargon pitch, compared to around 29% of high-status participants. In Study 2c, low-status participants used an average of 2.62 jargon terms, while high-status participants used an average of 1.48.

First Mention

Text: "see Fig. 1"

Context: This mention appears in the results and discussion section of Study 2a, after reporting the statistical analysis showing a significant relationship between status and jargon pitch selection. It directs the reader to the figure for a visual representation of this relationship.

Relevance: Figure 1 visually summarizes the key findings across multiple studies, demonstrating the consistent pattern of increased jargon use by low-status individuals. It supports the central hypothesis of the paper that low status leads to increased jargon use as a form of status compensation.

Critique
Visual Aspects
  • The use of separate bar charts for each study allows for clear comparison across different contexts and measures.
  • The consistent labeling of axes (Low Status, High Status) and the inclusion of error bars improve clarity.
  • The figure could be enhanced by adding more descriptive labels to each chart, indicating the specific measure being presented (e.g., '% Selecting High-Jargon Pitch').
Analytical Aspects
  • The figure effectively illustrates the main effect of status on jargon use across various studies.
  • The inclusion of error bars provides a visual representation of the variability in the data.
  • The figure would be stronger if it included information about the statistical significance of the differences between low and high status in each study.
Numeric Data
  • Study 2a: Low Status - High Jargon Pitch Selection: 40.8 %
  • Study 2a: High Status - High Jargon Pitch Selection: 29.2 %
  • Study 2c: Low Status - Jargon Terms Used: 2.62
  • Study 2c: High Status - Jargon Terms Used: 1.48

Study 2b: Replication study showing that low status increases jargon use

Overview

Study 2b replicates Study 2a, investigating the causal relationship between low status and jargon use in a simulated startup pitch competition. This study includes a manipulation check and a consistent audience composition to address limitations of the previous study. The results confirm that lower-status participants are more likely to choose high-jargon pitch descriptions.

Key Aspects

Strengths

Suggestions for Improvement

Study 2c: Low status increase jargon use during a synchronous conversation

Overview

Study 2c tested the hypothesis that low status increases jargon use in a live conversation setting. Participants were paired and assigned roles as either an Academic Researcher or a Non-Profit Representative. The Academic Researcher's status was manipulated (low or high), while the Non-Profit Representative served as a conversational partner. Researchers were given research summaries containing jargon and non-jargon equivalents, and their use of jargon during the conversation was measured. The study found that low-status researchers used significantly more jargon than high-status researchers.

Key Aspects

Strengths

Suggestions for Improvement

Study 2d: Low status increases acronym use

Overview

Study 2d experimentally tested the impact of status on acronym use among undergraduate business students. Participants imagined creating a professional profile for a networking platform, with their status manipulated by the described prominence of MBA students (low status) or incoming freshmen (high status). Low-status participants used more acronyms in their profiles, supporting the hypothesis that low status increases jargon use, specifically acronyms, as a form of status compensation.

Key Aspects

Strengths

Suggestions for Improvement

Study 3a: Evaluative concern as a mediator of the low status → Jargon use effect

Overview

Study 3a explores evaluative concern as a mediator between low status and jargon use. Participants, acting as researchers from low- or high-status schools, chose between jargon-laden and simpler titles for a conference presentation. Results showed low-status participants chose the jargon-heavy title more often, driven by a higher concern for audience evaluation.

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Figure 2

Figure 2, titled 'The effect of status on jargon use is mediated by evaluative concern, Study 3a,' is a path diagram illustrating the mediation model. It shows how status influences jargon use through evaluative concern. The diagram includes three variables: status (1 = low, 2 = high), evaluative concern, and jargon use. A solid arrow connects status to evaluative concern with a label of '-.90***' indicating a strong negative relationship. Another solid arrow connects evaluative concern to jargon use with a label of '.77***' indicating a strong positive relationship. A dotted arrow connects status directly to jargon use, and the label '-.50*/.01ns' below this arrow suggests a negative relationship that becomes non-significant when the mediator is included. The caption indicates that a bootstrapping mediation analysis revealed a significant indirect effect (bias-corrected 95% CI = [-0.11, -0.05]).

First Mention

Text: "a bootstrapping mediation analysis revealed that evaluative concern mediated the effect of status on jargon selection (bias-corrected 95% CI = [-0.11, -0.05]) (see Fig. 2)."

Context: This is the final sentence of the results and discussion subsection for Study 3a. It refers to the figure after stating the results of the mediation analysis.

Relevance: Figure 2 visually represents the key finding of Study 3a, supporting Hypothesis 2. It demonstrates that the effect of status on jargon use is mediated by evaluative concern, meaning that low status leads to increased evaluative concern, which in turn leads to greater jargon use.

Critique
Visual Aspects
  • The figure clearly presents the mediation model with appropriate use of arrows and labels.
  • The use of solid and dotted lines effectively distinguishes between direct and indirect effects.
  • The figure could be improved by providing a legend explaining the meaning of the asterisks indicating significance levels.
Analytical Aspects
  • The figure accurately reflects the results of the bootstrapping mediation analysis.
  • The inclusion of the confidence interval for the indirect effect strengthens the interpretation.
  • The figure would benefit from including the path coefficients and their significance levels directly on the diagram, rather than just in the caption.
Numeric Data
  • Path Coefficient: Status to Evaluative Concern: -0.9
  • Path Coefficient: Evaluative Concern to Jargon Use: 0.77
  • Direct Effect: Status to Jargon Use: -0.5
  • Bias-Corrected 95% CI for Indirect Effect: -0.11
  • Bias-Corrected 95% CI for Indirect Effect: -0.05

Study 3b: Replication study involving mediation in the context of legal jargon

Overview

Study 3b replicates the findings of Study 3a but within the context of legal jargon. It examines whether low status among trial lawyers leads to increased use of legalese and if this effect is mediated by evaluative concern. Participants were assigned to either a high- or low-status condition and asked to select a title for a presentation, one with and one without legalese. The study found that low-status participants were more likely to choose the title containing legalese, and this effect was mediated by evaluative concern.

Key Aspects

Strengths

Suggestions for Improvement

Non-Text Elements

Figure 3

Figure 3, titled 'The effect of status on legalese jargon use is mediated by evaluative concern, Study 3b', presents a path diagram illustrating the mediating role of evaluative concern in the relationship between status and the use of legalese jargon. The diagram depicts three variables: status (1 = low, 2 = high), evaluative concern, and legalese jargon use. A solid arrow connects status to evaluative concern, labeled '-.66**', indicating a significant negative relationship. Another solid arrow connects evaluative concern to legalese jargon use, labeled '.93***', indicating a significant positive relationship. A dotted arrow connects status directly to legalese jargon use, labeled '-.74*/.026ns', suggesting a negative relationship that becomes non-significant when the mediator is included. The caption mentions a significant indirect effect revealed by a bootstrapping mediation analysis (bias-corrected 95% CI = [-0.16, -0.03]).

First Mention

Text: "Furthermore, a bootstrapping mediation analysis revealed that evaluative concern mediated the effect of status on jargon selection (bias-corrected 95% CI = [-0.16, -0.03]) (see Fig. 3)."

Context: This mention appears at the end of the results and discussion section of Study 3b, after reporting a significant relationship between status and legalese title selection. It refers to the figure to visually represent the mediation analysis results.

Relevance: Figure 3 visually supports the hypothesis that evaluative concern mediates the relationship between status and legalese jargon use. It demonstrates that low status leads to increased evaluative concern, which in turn leads to greater use of legalese jargon. This finding strengthens the argument that jargon use, in this case legalese, serves as a status compensation mechanism.

Critique
Visual Aspects
  • The figure clearly illustrates the mediation model with standard path diagram conventions.
  • The use of solid and dotted lines effectively differentiates direct and indirect effects.
  • The asterisks indicating significance levels are helpful, but a legend explaining their meaning would enhance clarity.
Analytical Aspects
  • The figure accurately represents the statistical mediation analysis results.
  • The inclusion of the confidence interval for the indirect effect provides important information about the precision of the estimate.
  • The figure would be more informative if it included the path coefficients and their p-values directly on the diagram.
Numeric Data
  • Path Coefficient: Status to Evaluative Concern: -0.66
  • Path Coefficient: Evaluative Concern to Legalese Jargon Use: 0.93
  • Direct Effect: Status to Legalese Jargon Use: -0.74
  • Bias-Corrected 95% CI for Indirect Effect (Lower Bound): -0.16
  • Bias-Corrected 95% CI for Indirect Effect (Upper Bound): -0.03

Study 3c: Manipulating the mediator of evaluative concern

Overview

Study 3c experimentally tested the mediating role of evaluative concern in the relationship between status and jargon use. Researchers manipulated participants' communication goals, focusing them on either evaluative concern (impressing the audience) or communication clarity (ensuring understanding). Participants then chose between a high-jargon and a low-jargon title for a presentation. The study found that participants primed with evaluative concern were more likely to select the high-jargon title, supporting the hypothesis that evaluative concern drives the low-status-jargon link.

Key Aspects

Strengths

Suggestions for Improvement

General discussion

Overview

This section summarizes the findings of the nine studies presented in the paper, highlighting the consistent relationship between low status and increased jargon use. It discusses the theoretical contributions of the research, identifying jargon use as a novel form of status compensation, termed "compensatory conspicuous communication." The discussion also acknowledges limitations of the studies and suggests future research directions.

Key Aspects

Strengths

Suggestions for Improvement

Conclusion

Overview

The conclusion summarizes the research findings, emphasizing the link between low status and increased jargon use. It highlights the theoretical contribution of identifying "compensatory conspicuous communication" as a novel form of status compensation. The conclusion also acknowledges limitations and suggests future research directions, including exploring non-linear relationships with status, audience effects, and the potential for jargon to obfuscate.

Key Aspects

Strengths

Suggestions for Improvement

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