Target Statements Research Articles

Economic growth and environmental pollution in China: New evidence from government work reports

In China, economic growth targets significantly affect the economic behavior of local governments. This paper analyzes a dataset of the economic growth targets from 230 city government work reports from 2004 to 2019 to reveal how economic growth targets affect local environmental pollution. The empirical results show that the economic growth targets are “overweight” from the higher-level governments to the lower-level governments, which significantly aggravates regional environmental pollution because of environmental regulation relaxation, blocked industrial structure upgrades and technological innovation inhibition. Furthermore, to exceed the economic growth targets, local governments usually adopt the “riding a seesaw” strategy for the treatment of different pollutants. If the economic growth target statements are ambiguous or attainable, then environmental pollution is reduced. Interestingly, the “preemptive” city government, which sets economic growth goals before its province, is more inclined to maintain growth at the expense of the environment. This study provides important evidence for the literature on the impacts of government behavior on environmental pollution.

Can mental imagery boost the effect of the positive cognitive bias modification of interpretation (CBM-I) on interpretation bias and memory bias?

Background and objectivesCognitive bias modification of interpretation (CBM-I) has been widely used and yielded mixed results. This experiment explored the unique role of mental imagery in positive CBM-I. Methods60 participants (M = 23.13, SD = 1.04) were randomly assigned to a imagery-based positive CBM-I group (imagery group) and a conventional verbal-based positive CBM-I group (control group). The imagery group received additional practice in generating mental imagery and were instructed to fully focus on the imagery during the formal training. The dependent variables included interpretation bias (probe latencies and similarity ratings for recognition task), memory bias, and intrusive memory. Results(1) For the positive probe scenario, the reaction time of the two groups was shorter in the posterior five blocks than the anterior five blocks. However, the difference in latency between pre- and post- training for the imagery group was larger than that of the control group; (2) For the recognition task, the positive target statement score was significantly higher, while the negative one was significantly lower for the imagery group than that of the control group (3) The imagery group (vs. control); showed more beneficial effects on memory bias. LimitationsThe limitations consisted of the difference in time of the manipulation between the two groups, the richness of the imagery operationalization, generalizability, and the lack of pre-manipulation of interpretation bias assessments. ConclusionsThe imagery-based CBM-I led to more positive interpretation biases, less negative interpretations, and more positive memory biases, indicating that mental imagery can boost the effect of the positive CBM-I.

Only true and fabricated baseline statements combined might improve lie, but not truth, detection.

We tested the effect of true and fabricated baseline statements from the same sender on veracity judgments. We predicted that presenting a combination of true and fabricated baseline statements would improve truth and lie detection accuracy, while presenting a true baseline would improve only truth detection, and presenting a fabricated baseline would only improve lie detection compared with presenting no baseline statement. In a 4 × 2 within-subjects design, 142 student participants (Mage = 23.47 years; 118 female) read no baseline statement, a true baseline statement, a fabricated baseline statement, and a combination of a true and a fabricated baseline statement from 29 different senders. Participants then rated the veracity of a true or fabricated target statement from the same 29 senders. Logistic mixed-effects models with senders and participants as random effects showed no significant differences in overall veracity judgment accuracy between the no-baseline (51%) and either the true-baseline (44%) or the fabricated-baseline (49%) conditions. Equivalence tests failed to show the predicted equivalence of these accuracy rates. Separate analyses of truth and lie detection rates confirmed the assumed improvement of lie detection in the combination-of-true-and-fabricated-baseline condition (accuracy = 39%-61%). No other truth or lie detection rate changed significantly except that, unexpectedly, a true baseline reduced truth detection accuracy (64%-49%). Baseline statements largely did not affect judgment accuracy and, in the case of true baselines, even had a negative impact on truth detection. The rather small positive effect of two baseline statements on lie detection suggests an avenue for further research, especially with expert raters. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Golden Mutator Recommendation Based on Mutation Pattern Mining

Mutation testing is widely used in the research of evaluation and optimization of test set quality, and has been paid attention to the study of bug localization and fixing. But one inherent problem of mutation testing is huge computation cost. Selective mutation is an important method to reduce mutation testing cost. However, the existing selective mutation researches indicate that there is no universal selection strategy. This paper proposes a method which integrates with historical software data mining to recommend suitable mutator for program under test. The basic idea of the method is in the software version control system, any pair of nonfixed and post-fixed programs can be original program and mutant of each other. The edit performed during bug fixing contains mutators, and such mutator can guide buggy program to correct program, hence it is called Golden Mutator. The basic method is to compare the buggy files and the corresponding fixed files in the version control system, obtain historical faulty statements and their fix editing operations, thereby accumulating the bug-fix instance base, and then mining mutation patterns from it. Before mutating the target statement, we first find out faulty instances similar to the target statement, and use their fixing edits to match with the mutation pattern, so as to get the golden mutator applicable to the target statement. This paper uses Defects4j dataset in the test, verifies the accuracy of the proposed recommendation method, and further uses the method in bug localization. Compared to fixedly selected mutators, when applying the golden mutator recommended by using the proposed method, the average accuracy of bug localization is higher.

Detecting deception using comparable truth baselines

ABSTRACT Baselining – comparing the statements of interest to a known truthful statement by the same individual – has been suggested to improve lie detection accuracy. A potential downside of baselining is that it might influence the characteristics of a subsequent statement, as was shown in previous studies. In our first experiment we examined this claim but found no evidence that a truthful baseline influenced the characteristics of a subsequent statement. Next, we investigated whether using a truthful baseline statement as a within-subject comparison would improve lie detection performance by investigating verbal cues (Experiment 1) and intuitive judgements of human judges (Experiment 2). Our exploratory analyses showed that truth tellers included more auditory and temporal details in their target statement than in their baseline than liars. Observers did not identify this verbal pattern. Exposure to a truthful baseline statement resulted in a lower truth accuracy but no difference in lie accuracy.

The ability to recognise emotions predicts the time-course of sarcasm processing: Evidence from eye movements.

A core feature of sarcasm is that there is a discrepancy between the literal meaning of the utterance and the context in which it is presented. This means that a sarcastic statement embedded in a story introduces a break in local coherence. Previous studies have shown that sarcastic statements in written stories often elicit longer processing times than their literal counterparts, possibly reflecting the difficulty of integrating the statement into the story's context. In the present study, we examined how sarcastic statements are processed when the location of the local coherence break is manipulated by presenting the sarcastic dialogues either before or after contextual information. In total, 60 participants read short text paragraphs containing sarcastic or literal target statements, while their eye movements were recorded. Individual differences in ability to recognise emotions and working memory capacity were measured. The results suggest that longer reading times with sarcastic statements not only reflect local inconsistency but also attempt to resolve the meaning of the sarcastic statement. The ability to recognise emotions was reflected in eye-movement patterns, suggesting that readers who are poor at recognising emotions are slower at categorising the statement as sarcastic. Thus, they need more processing effort to resolve the sarcastic meaning.

Reducing scheduling sequences of message-passing parallel programs

Context: Message-passing parallel programs are commonly used parallel programs. Various scheduling sequences contained in these programs, however, increase the difficulty of testing them. Therefore, reducing scheduling sequences by using appropriate approaches can greatly improve the efficiency of testing these programs.Objective: This paper focuses on the problem of reducing scheduling sequences of message-passing parallel programs, and presents a novel approach to reducing scheduling sequences.Method: In this approach, scheduling sequences that affect the target statement are first determined based on the relation between a scheduling sequence and the execution of the target statement. Then, these scheduling sequences are divided into a number of equivalent classes according to the execution of the target statement. Finally, for each scheduling sequence in the same equivalent class, the values of the two proposed indexes are calculated, and the scheduling sequence with the minimal comprehensive value is selected as the one after reduction.Results: To evaluate the performance of the proposed approach, it is applied to test 12 typical message-passing parallel programs. The experimental results show that the proposed approach reduces 63% scheduling sequences on average. And compared with the method without reduction, and the method with randomly selecting scheduling sequences, the proposed approach shortens 67% and 52% execution time of a program for covering the target statement on average, respectively.Conclusion: The proposed approach can greatly reduce scheduling sequences, and shorten execution time of a program for covering the target statement, hence improving the efficiency of testing the program.

Uncanny sums and products may prompt “wise choices”: Semantic misalignment and numerical judgments

Automatized arithmetic can interfere with numerical judgments, and semantic misalignment may diminish this interference. We gave 92 adults two numerical priming tasks that involved semantic misalignment. We found that misalignment either facilitated or reversed arithmetic interference effects, depending on misalignment type. On our number matching task, digit pairs (as primes for sums) appeared with nouns that were either categorically aligned and concrete (e.g., pigs, goats), categorically misaligned and concrete (e.g., eels, webs), or categorically misaligned concrete and intangible (e.g., goats, tactics). Next, participants were asked whether a target digit matched either member of the previously presented digit pair. Participants were slower to reject sum vs. neutral targets on aligned/concrete and misaligned/concrete trials, but unexpectedly slower to reject neutral versus sum targets on misaligned/concrete-intangible trials. Our sentence verification task also elicited unexpected facilitation effects. Participants read a cue sentence that contained two digits, then evaluated whether a subsequent target statement was true or false. When target statements included the product of the two preceding digits, this inhibited accepting correct targets and facilitated rejecting incorrect targets, although only when semantic context did not support arithmetic. These novel findings identify a potentially facilitative role of arithmetic in semantically misaligned contexts and highlight the complex role of contextual factors in numerical processing.

Less specific recovery strategy targets for threatened and non-charismatic species at risk in Canada

AbstractRecovery strategies for species at risk have been criticized for a lack of specificity (i.e. measurable and quantifiable criteria) as well as for taxonomic biases, both of which may ultimately affect species’ recovery. However, it is unknown whether the clarity and specificity of written statements within recovery strategies can also influence recovery efforts for certain species at risk. To assess this we examined the variation in semantic uncertainty in the target statements of recovery strategies for Canadian species at risk at the federal and provincial levels. We quantified the lexical density and readability of recovery target statements and examined them for differences according to taxonomic grouping, jurisdiction and degree of endangerment. Recovery statements for the category threatened species had greater semantic uncertainty than those for higher (endangered) and lower (special concern) categories, which is likely to be a function of the fact that threatened species are less abundant than special concern species but are subject to greater errors in population estimates than endangered species. We also found that recovery statements for non-charismatic species (e.g. plants and invertebrates) had greater semantic uncertainty than those for other taxa, which may be related to the resources available for studying and conserving them. Our results suggest a need for greater specificity in recovery targets for threatened and non-charismatic species, and that more focused data collection on these species’ populations is warranted.

Are you as good as me at telling a story? Individual differences in interpersonal reality monitoring

We tested whether someone's ability to tell a good story, in terms of the Reality Monitoring (RM) tool, affects the way s/he judges the stories told by others. Forty participants (undergraduate students) wrote down two statements – one about activities they did 30 minutes ago, and the other about a past event. Subsequently, they rated the quality of a target statement written by someone else. We found that the tendency to provide a not so detailed or a very detailed statement was stable across the two statements the participants wrote. Furthermore, this tendency affected how they judged the target statements: The richer a participant's statements were compared to the target statement, the more critical the participant was in judging the target statement. These findings imply that RM is subject to biases which are related to individual differences. We discuss the implications of these findings for applying the RM lie detection tool in the field.

Validating Contradiction in Texts Using Online Co-Mention Pattern Checking

Detecting contradictive statements is a foundational and challenging task for text understanding applications such as textual entailment. In this article, we aim to address the problem of the shortage of specific background knowledge in contradiction detection. A novel contradiction detecting approach based on the distribution of the query composed of critical mismatch combinations on the Internet is proposed to tackle the problem. By measuring the availability of mismatch conjunction phrases (MCPs), the background knowledge about two target statements can be implicitly obtained for identifying contradictions. Experiments on three different configurations show that the MCP-based approach achieves remarkable improvement on contradiction detection and can significantly improve the performance of textual entailment recognition.

Comparative performance evaluation of applying extended PIE technique to accelerate software testability analysis

The rapid development of technology provides high performance and reliability for the hardware system; based on this, software engineers can focus their developed software on more convenience and ultra-high reliability. To reach this goal, the testing stage of software development life cycle usually takes more time and effort due to the growing complexity of the software. How to build software that can be tested efficiently has become an important topic in addition to enhancing and developing new testing methods. Thus, research on software testability has been conducted and various methods have been developed. In the past, a dynamic technique for estimating program testability was proposed and called propagation, infection and execution (PIE) analysis. Previous research studies have shown that PIE analysis can complement software testing. However, this method requires a lot of computational overhead in estimating the testability of software components. In this article, we propose an extended PIE (EPIE) method to accelerate the conventional PIE analysis, based on generating group testability as a substitute for statement testability. Our proposed method can be systematically separated into three steps: breaking a program into blocks, dividing the blocks into groups and marking target statements. Experiments and evaluations with the Siemens suite, together with cost-effectiveness analysis, clearly show that the number of analysed statements can be effectively decreased, and the calculated values of testability are still acceptable.

Testability transformation based on equivalence of target statements

The application of genetic algorithms in automatically generating test data has become a research hotspot and produced many results in recent years. However, its applicability is limited in the presence of flag variables. This issue, known as the flag problem, has been studied by many researchers to date. We propose a novel method of testability transformation to tackle the flag problem. Different from traditional transformation methods, in our method, the key step is not the transformation of source code, but that of target statements. We search for a new target statement (or a set of target statements) equivalent to the original one and then transform the problem of generating test data that cover the original target statement into the one that cover the new target statement (or a set of target statements). We apply our method in many real-world programs, and the experimental results show its effectiveness.

How generalization inferences are constructed in expository text comprehension

Three questions regarding adult readers’ processing of generalization inferences (conceptually broad statements that subsume several specific statements) are investigated. College students ( N = 193) read expository texts containing target statements that were consistent, inconsistent, or off-topic in relation to a generalization implied by one paragraph. Reading times were faster for consistent than inconsistent statements and faster for inconsistent than off-topic statements, indicating adult readers construct generalization inferences online during initial reading of a text and that the inference they construct is relatively narrow in scope. This pattern of faster reading time for consistent sentences occurred under different reading goals, suggesting generalization inferences are a pervasive component of expository text comprehension.

Advanced chopping of sequential and concurrent programs

A chop for a source statement s and a target statement t reveals the program parts involved in conveying effects from s to t. While precise chopping algorithms for sequential programs are known, no chopping algorithm for concurrent programs has been reported at all. This work introduces six chopping algorithms for concurrent programs, which offer different degrees of precision, ranging from imprecise over context-sensitive to time-sensitive. Our evaluation on concurrent Java programs shows that context-sensitive and time-sensitive chopping reduces chop sizes significantly. We further present an extensive evaluation of chopping algorithms for sequential programs and describe a new, easy-to-implement chopping technique for sequential programs that computes fast and almost context-sensitive chops.

Understanding Verbal Irony: Clues From Interpretation of Direct and Indirect Ironic Remarks

Recently, irony researchers have emphasized that irony interpretation involves metarepresentational inferencing in order that the perceiver can determine whether the speaker's attitude is counterfactual to their statement. This research investigated whether the perception of irony also depends on the extent to which an ironic statement is suitably face-threatening in its particular context. Target statements were direct and indirect ironic remarks, and context conditions were modulated on 2 dimensions: context incongruity (strong vs. weak) and speaker–target relationship (close vs. distant). This study examined interpretations of ironic criticisms (Experiments 1 and 2) and ironic compliments (Experiment 3). Results showed evidence that suitable face-threat was important to a perception of irony: In some contexts (strongly incongruent context and close speaker–target relationships), irony was perceived more strongly for direct ironic remarks; and in other contexts (weakly incongruent context and distant speaker–target relationships), irony was perceived more strongly for indirect ironic remarks.

The Effect of Board Independence on Target Shareholder Wealth

We seek insights into whether, and if so how, an independent board enhances the bid premiums offered to target firm shareholders during a takeover. The results indicate that the presence of an independent board enhances the initial bid premium by, on average, 21.1%. However, the results of more refined analysis suggest that the enhanced bid premium is in fact driven by independent boards comprising non‐executive directors who have reputation capital at stake. We also find that independent boards that resist takeovers or include voluntary independent expert reports in target statements, increase the bid premium revision by, on average, 15.6% and 16.2%, respectively.

When vying reveals lying: the timed antagonistic response alethiometer

AbstractTwo experiments tested a new computer‐based lie‐detection technique. The Timed Antagonistic Response Alethiometer (TARA) manufacturers a situation in which, if respondents lie, they must perform two incompatible tasks, whereas if they tell the truth, they can perform two compatible ones. Both tasks involve repeatedly classifying target and control statements as true or false. The incompatible task combination, being more difficult, takes longer to complete correctly; hence, slower responses diagnose dishonesty. Experiment 1 found that, while concurrently classifying control statements honestly, participants invariably took longer to classify target statements dishonestly than honestly. Exploiting this effect, Experiment 2 found that separate groups of liars and truth‐tellers could be distinguished with about 85% accuracy. The properties and potential of the technique are discussed. Copyright © 2006 John Wiley & Sons, Ltd.

Assessing the Effects of Adding Messages to Warning Labels

Within the context of a realistic task (setting up an office space), 84 subjects used a two-drawer file cabinet that displayed a warning label with different numbers of statements—one, three or five. In each of these labels, a target statement, indicating that the bottom drawer was to be filled before the top one to avoid tipping, appeared first in the list. One additional warning label condition had three statements with the target statement appearing last. The warning label was affixed to the file cabinet in such a way that subjects had to interact with and remove it in order to fill the file drawer(s). Results demonstrated that almost all of the subjects noticed the label, but very few read or complied with the target warning statement regardless of its location within the list (first or last) or the number of total items on the label (one, three or five).

Discourse Factors That Influence Online Reading of Metaphor and Irony

Statements such as "children are precious gems" can be interpreted as either a metaphor (children are valuable) or as a sarcastic comment on the metaphor (children are a burden). Katz and Pexman (1997) identified several constraints that biased readers toward either the metaphoric or the sarcastic-ironic interpretation: nature (occupation) of the person making the statement, whether the statement was counterfactual to information in the preceding discourse context, and whether the root metaphor instantiated in the statement was familiar. In this experiment we investigated whether these constraints would be used online during normal reading. In a moving window reading task, results showed that readers used the constraints early in processing the target statement and took longer to resolve the ironic (relative to the metaphoric) sense of the target statement. Also, data from the online reading measures were strongly correlated with ratings and memory data obtained by Katz and Pexman.